Hoodies You Can See Through

PCR with FactoMineR dynGraph

There are two ways of looking at the graphic representation of data in Data Mining. The first is to consider it as a tool for presenting results. The graph supports the text and tables to highlight the information produced by analysis. For example, one text ad in the sales of caps increases in winter a small curve where there are peaks and end sales earlier this year confirms that.

The second seeks to integrate the graph in the same exploratory process. Here, it becomes an additional tool for detecting patterns, peculiarities and relationships that may exist in the data. In this regard, modern software with graphics capabilities of increasingly powerful, open up incredible opportunities. As I often say a graph is widely felt much better than a series of ratios to interpret confusing or poorly controlled.

In this tutorial, we conducting a principal components analysis with the software R. We had already done previously with the procedure princomp () . Here we repeat the study with the procedure (PCA) package FactoMineR. Many indicators on the elements (variables, individuals) are active or illustrative provided directly now, greatly facilitating the task of the practitioner. It is no longer necessary to post-calculated using formulas more or less complex as we have done in previous document. Subsequently, on the basis of indicators delivered by PCA (), we will conduct an exploration using graphical Tool dynGraph eponymous package. We find that the opportunities for interactive analysis are numerous.

Keywords: R software, principal component analysis, PCA, correlation circle, illustrative variables, FactoMineR, dyngraph, interactive graphical analysis
components: PCA, dynGraph
Link: acp_avec_factominer_dyngraph.pdf
Data : acp_avec_factominer_dyngraph.zip
References:
G. Saporta, "Probability, Data Analysis and Statistics", Dunod, 2006, pages 155 to 179.
Tutorial Tanagra, " ACP - Description of vehicles "
F. Husson, J. Josse, S. Le, J. Pages FactoMineR The package for R; http://factominer.free.fr/
S. Le, J. Durand, dynGraph The package for R; http://dyngraph.free.fr/

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and Tools for application development

A tutorial a little different this time. I talk about tools and programming languages for developing data mining applications.

Start a discussion about "the best programming language" is an excellent way to fill an evening computer. The underlying question is "what is the language that develops applying the most powerful, fastest ... ".

Very good boy, the atmosphere quickly becomes stormy, or even harmful. Some people, very charming for the most part, behave passionate, even passionate, rise on their high horse (tagada, tagada) in Assen arguments sometimes completely irrational. I know whereof I speak, I am when I let myself go. Yet, ultimately, in deciding what kind of debate would be pretty easy. It sufficient to characterize the problems that we seek to solve, write an equivalent code in different languages, and study the behavior of l'exécutable généré. C'est ce que nous allons faire dans ce didacticiel en nous plaçant dans deux situations couramment rencontrées lors de la programmation d'algorithmes d'exploration de données. On verra que le résultat n'est pas du tout celui qu'on attendait (si on en attendait un, ouh là là je vois déjà certains bondir), loin de là.

Tout d'abord, corrigeons un abus de langage (si je puis dire), la performance n'est pas une affaire de langage, mais plutôt une affaire de technologie et de compilateur. Nous le verrons, le même code source, compilé avec des outils différents, peut aboutir à des exécutables avec des comportements très différents. We will study in this paper: C # with Visual C # Express Edition of Microsoft Pascal using Borland Delphi 6.0, Pascal with the Free Pascal Compiler 2.2.4 Lazarus 0.9.28, C + + with Borland C + + Builder 4, C + + with Dev C + + (compiler G + +) ; executed via Java JRE1.6.0_19 Windows (Eclipse development tool I used). All these tools except Borland C + + Buile 4, are available free on the net. For all, I have selected the options that optimize the compilation speed.

Performance is evaluated by measuring the time calculations executables launched through the shell outside the IDE (Integrated Development Environment) to avoid interference. My machine is multi-heart, user time and CPU time are almost the same. We content ourselves with the first. Each program is run 10 times. We calculate the average.

Keywords: programming language, c + +, C #, Delphi, pascal, java
Tutorial: fr_Tanagra_Programming_Language.pdf
Source Code: programming_language.zip

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Association Rules - Transactional Data

The mining association rules is one of the flagship applications of data mining. The idea is update patterns, as co-occurrences in the database. The emblematic example is the analysis of receipts from supermarkets: they want to discover the rules of behavior such as "if the customer bought diapers and wipes, it will buy milk for growth." In which case it may be appropriate to the proper rays in the same area of the store (this is the case with regard to the supermarket I frequent usually). The "if" the rule is called "history", the "so what" is "therefore." It

is possible to find co-occurrences in the individual tables - variables that are manipulated with the usual data mining software. But often, especially through the induction of association rules, data can be in the form of a transactional basis. If we take the example of the analysis of receipts, we have a list of products by cart.

This data representation is quite natural in view of the problem we want to capture. It also has the advantage of being more compact since only the products listed are actually observed in each cart. We need not concern ourselves with products that are not, especially since they can be very numerous if one refers to the number of items that can offer a brand from supermarkets.

As far as this mode of description is natural, it turns out that many programs do not know apprehend directly. We observe curiously a real division between vocational and tools to those from academia. The first most of them can handle this file type. This is the case of software SPAD 7.3 and SAS Enterprise Miner 4.3 we study in this tutorial. The latter, however, require a prior transformation of data to work. We use a VBA macro running in Excel to transform our data base "individuals - Variable Bit suitable for treatment under Tanagra 1.4.37 and 2.2.2 Knime . Attention, we must respect the original specifications, ie focus only on rules indicating the simultaneous presence of products in shopping carts. There is no question, following a coding 'present - absent "poorly controlled, to produce rules highlighting the simultaneous absence of certain products. This may be interesting in some cases, but this is not the purpose of our analysis.

Keywords: association rule, association rules, SPAD 7.3, lock em 4.3, 2.2.2 Knime, filtering rules, lift
Components: A PRIORI
Tutorial: fr_Tanagra_Assoc_Rule_Transactions. pdf
Data : assoc_rule_transactions.zip
References:
Wikipedia, "Association rule learning "

» Tom Et Lola «

EPISODE 14 SEASON 6 (VO)

14/14 EPISODE SEASON 6 (VO): approx. 90 min

"CARPE DIEM (SEGUNDA PARTE)"

SEASON FINALE

SEE EPISODE:
\u0026lt;Previous the need to install Adobe Flash Player

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decision trees on large files (update)

In a post very old (" processing large volumes - Comparison Software "- September 2008), I compared the behavior of several software when processing a file with relatively large decision trees.

I was describing inter alia the conduct of Tanagra 1.4.27 version released in August 2008. Since my development machine has changed Tanagra itself has changed, we are so far to version 1.4.37, and Sipina has also been modified (version 3.5), with the introduction of multithreading induction techniques for certain trees. I thought it was time to study the performance by re-editing experiments in the same conditions. On

Sipina Tanagra and the only software I have analyzed in this new, improved processing time is obvious. After, we must discern what is attributable to the change machine, which amounts to changes in implementations. We propose some tracks in our document.

The new results were added in the last section (Section 5) of the PDF.

Link: fr_Tanagra_Perfs_Comp_Decision_Tree.pdf

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(No) Supreme! (Corrigendum)

According to reliable information fairly, Reynolds, Newell and his ilk do not cater to quash. We have those who filed complaints with the tribunal, won! It's final. I will return later on, when I really official proof! Well, we can expect a little money for Christmas (not Newell, beware!). Thank you again tou (te) s those who through their advocacy, their courage and conviction, we made this victory possible. A special thank you to Mr Meyer, who has committed well beyond what is entitled to expect from a lawyer. Naturally, this is a page is turned. I will see by cons always with great pleasure that the protagonist is indeed a human adventure. This story is over, but life, the true, she continues!

CORRIGENDUM!

I just received an appeal! So it repartu for a ride! Nevertheless, they must however pay! Go, we believe it !!!!!

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EPISODE 13 SEASON 6 (VO)


13/14 SEASON EPISODE 6 (VO):
approx. 90 min

"CARPE DIEM (PRIMERA PARTE)"

SEE EPISODE:

\u0026lt;Previous

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The World Bedding Bedding

The world of bedding or the comeback of Ben Harrous!

5 years imprisonment, a fine of 375,000 euros: this is a crook ... qu'encourt

www.le mondedelaliterie .

en

you like The scam Bedding Voltaire, scam Best bedding (bankruptcies on 28 January 2010 and September 2 2010), you'll love World of bedding!

Imagine the gang Harrous Ben is back in a new shop just opposite the metro Bel Air, 32 boulevard de Picpus à Paris 12e. Toujours les mêmes procédés: un site Internet avec de fausses promotions, de faux déstockages, de faux prix sacrifiés, de fausses dates (2004, alors que la société vient d'être créée. 2004, c'est la date de création de MKB distribution, en liquidation judiciaire).

Aux commandes, les mêmes inénarrables Yohan Ben Harrous, le fils, Jean-Jacques Ben-Harrous, le père, Marianne Ben Harrous, née Bouaziz, la mère!!! On ne change pas une équipe qui gagne! On peut leur téléphoner au 01 43 47 15 86 pour leur faire un petit coucou.

To track galleys encountered by their customers, you can click here or here or there , here or there .

What family does not it?!

Always the same formula that made its success: you order a bed, they cashing the check and do not deliver the goods. Voila. Cashing money, bankruptcy fraud, and three months later we opened a new shop. He had to think it is not?!

note, low prices are only to attract customers ...

I tell you, you'll love it!

The company in question is called thus First Service (RCS Paris B 522 803 667). His number is 522803667000667 Siret.

Its capital is the amount of 5000 euros. The company was registered June 7, 2010.

course, you can check all this on societe.com.

The Ben Harrous sont les spécialistes de l'enfumage. Ils passent un temps fou à se faire référencer sur les sites commerciaux. Ainsi par exemple sur http://www.lesnewsdunet.com/lesactus/communique-1288010277.html

après un long et vibrant hommage à l'importance du sommeil, Ben Harrous donne le numéro de téléphone en se faisant appeler "Contact presse : Monsieur Petit", puis suit le numéro de téléphone de la boutique.

A hurler de rire!!

La famille Ben Harrous est spécialisée dans la faillite frauduleuse depuis longtemps. Voyons plutôt comment elle a fait ses premiers pas. Voici le détail. It's been twenty years since it lasts!

Yohan Harrous Ben (the son) has created two other companies: Decoration and shade (August 2009) and Galaxy 98 (this is an SCI).

NAME - Name Address JJB RELEASE
24 R-75017 PARIS BARON
17E__ARRONDISSEMENT

Legal Form SARL - CJ: 54 Date of creation

05/1987 Number of institutions 1
Business Activity:
- ( NAF rev.2)
Other specialized retail cce. Miscellaneous - NAF: 4778C
- (NAF rev.1)
Miscellaneous Retail Stores magasin - NAF : 524Z

Activite de l'etablissement :
- (NAF rev.2)
Autres cce de détail spé. divers - NAF : 4778C
- (NAF rev.1)
Commerces de détail divers en magasin - NAF : 524Z
Statut de l'etablissement Siège ou établissement principal
Type d'exploitation Propriétaire exploitant direct
Code topographique 75117
Departement du siege 75

Principal dirigeant BOUAZIZ Marianne
Fonction Gérant

Procédure collective ou amiable présente
dans l'historique des annonces : OUI (voir les Informations Légales)

Faillite personnelle
Date d'entrée Altares : 10/08/1990 - Source BODACC A: Listing No. 2755 of 08.07.1990


June 12, 1990 Judgement declaring bankruptcy personnelle.apour 10 years BOUAZIZ Marianne Address: resident 1 / 13, rue de la Noue 93170 Bagnolet Manager of the company JJB Distribution


Judicial Liquidation
Altares Date: 28/12/1989 - Source BODACC A: Listing No. 2599 27/12/1989


November 21, 1989 Judgement ordering the liquidation Judicial RCS Bobigny B 340 857 234 RC RC 88-B 05 789 JJB BROADCAST Address: 114 rue de Paris 93100 Montreuil-sous-Bois Me Moyrand Address: 22, avenue de la Division Leclerc, 93012 Bobigny Cedex statements of debts are to be filed within four months following this publication from the liquidator



BEST BED
Teaches BEDDING VOLTAIRE
Address 140 BIS RUE DE RENNES
75006 PARIS 06

No. RC: 07B09623
Health Legal SARL - CJ: 5499 7500 Euro Capital

Date Created Number 05/2007
establishment of two Business Activity
:
- (NAF rev.2)
Other specialized retail cce. Miscellaneous - NAF: 4778C
- (NAF rev.1)
Retailer Miscellaneous store - NAF: 524Z

activity of the establishment:
- (NAF rev.2)
Other specialized retail cce. Miscellaneous - NAF: 4778C
- (NAF rev.1)
Retailer Miscellaneous store - NAF: 524Z
Staff Headquarters of the institution or principal operating
Type Owner Operator
Department of seat 75

Principal Officer Marianne BOUAZIZ
Function Manager
Date and place of birth 11/12/1951 in Tlemcen (Algeria)

Procedure collective or mutual
present in the history of ads: YES (see Disclaimer)



Judicial Liquidation
Altares Date: 29/09/2010 - Source BODACC A No: 189: Listing No. 2094 29/09/2010
Court: TC PARIS CEDEX 04

Date: September 2, 2010. Judgement opening liquidation. 497 751 354 RCS Paris. BEST BED. Form: Limited Liability Company. Activity: Sales of bedding and accessories, furnishings and decorations, linens, curtains and curtain. Address: 140 bis rue de Rennes 75006 Paris. Completion of Judgement: Judgement declaring the judicial liquidation , date of insolvency August 6, 2010 appointing liquidator SELAFA Myah in the person of Mr. Patrice Frechou 102 rue du Faubourg Saint-Denis 75479 Paris Cedex 10 Cs10023. Statements Claims are to be submitted to the liquidator within two months of this publication.



MKB DISTRIBUTION
Teaches BEDDING VOLTAIRE
Address 20 rue Godefroy Cavaignac 75011 PARIS 11


No. RC: 04B11561
Legal Form SARL - CJ: 5499 7500 Euro Capital


06/2004 Date Created Number of establishment 1
Business Activity:
- (NAF rev.2)
Cce Wholesale (cce interent.) other well - NAF: 4649Z
- (NAF rev.1)
comm.gros Other consumer goods - NAF : 514S

activity of the establishment:
- (NAF rev.2)
Cce Wholesale (cce interent.) other well - NAF: 4649Z
- (NAF rev.1)
comm.gros Other consumer goods - NAF: 514S
Status headquarters or principal establishment
Operation Type Owner Operator
Department of seat 75

Principal Officer BEN Jean-Jacques HARROUS
Function Manager
Date and place of birth 15/12/1947 in Oran (Algeria)



Procedure collective or mutual
present in the history of ads: YES (see Disclaimer)

liquidation Starter
Altares Date: 26/02/2010 - A Source BODACC No.: 039: Listing No. 3144 25/02/2010
Court: TC PARIS CEDEX 04

Date: January 28, 2010. Another trial opening. 454 094 798 RCS Paris. MKB DISTRIBUTION. Form: Limited Liability Company. Activity: The sale of bedding and accessories, furniture, linen Demaison, curtains and draperies, appliances and any article Generalementde bazaar. Address: 140 bis rue de Rennes 75011 Paris. Completion of Judgement: Judgement declaring the judicial liquidation simplified, the date of termination payments 28 July 2008 appointing liquidator Brouard SCP-Daude me in the person of Xavier Brouard 34 rue Sainte-Anne 75001 Paris. Statements of claims are to be submitted to the liquidator Inthe two months of this publication.


NAME - Name FIRST SERVICE
Teaches THE WORLD OF THE BED
Address 32 BOULEVARD PICPUS
75012 PARIS

No. RC: 10B11870
Legal Form LLC-man - CJ: 5498
Capital 5,000 euros
Creation date 06 / 2010
Number of institutions 1
Business Activity:
- (NAF rev.2)
Cce Wholesale (cce interent.) textiles - NAF: 4641Z
- (NAF rev.1)
Wholesale of textiles - NAF: 514A

activity of the establishment:
- (NAF rev.2)
Cce Wholesale (cce interent.) textiles - NAF: 4641Z
- (NAF rev.1)
Wholesale of textiles - NAF: 514A
Staff Headquarters of the institution or principal operating
Type Owner Operator
Department of seat 75

Main BEN HARROUS leader Jean-Jacques
Function Manager
Date and place of birth 15/12/1947 in Oran (Algeria)

How Collective
this amicably or in the history of ads: NO

No Clearance for First Judicial Department, name of the company that The world teaches for bedding , Bld Picpus in Paris, but it's only a matter of time!

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EPISODE 12 SEASON 6 (VO)

ÉPISODE 12/14 SAISON 6 (VO):
durée environ 90 min "DECISIONES"

VOIR L'EPISODE: < Précédent

LAST CHECK NO VALIDITY
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Multithreading for decision trees

Much of modern PCs are equipped with multi-core processors. In fact, the computer operates as if had multiple processors. Some also big servers in particular, have effectively. Software and data mining algorithms must be developed in order to benefit. Currently, few tools are widely available that exploit these new features of machines.

Indeed, the case is not simple. It is impossible to develop a generic approach that would be valid regardless of the learning method used. For a given technology, decompose an algorithm into tasks that can execute in parallel is a research field in itself. Scientific publications full of proposals of all kinds, both methodology (modified algorithm) at the technological level (implementation on machines). A large majority of them are mainly interested in the implementation of large systems. There are very few proposals for lightweight solutions that can be easily introduced on software for personal computers.

In this tutorial, a solution based on threads is highlighted. It is located in version 3.5 of Sipina.

Keywords: multithreading, thread, threads, decision trees, CHAID, SIPINA 3.5, 2.2.2 Knime, RapidMiner 5.0.011
Tutorial: fr_sipina_multithreading.pdf
Data : covtype.arff.zip
References:
Wikipedia, "Decision trees "
Aldinucci, Ruggieri Torquati, "Porting Decision Tree Algorithms to Multicore using FastFlow ", PKDD-2010.

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Creating reports with Tanagra

Reporting is a true test of differentiation between software data mining vocational and those derived from research. To a practitioner (eg research officer), it is important to be able to easily recover the result of his work in a process text or in a slideshow. The case becomes particularly interesting when it already has an output in spreadsheet format. Indeed the results are often presented in the form of various tables and possibly graphics. The ultimate is to define in advance models of relationships that are fed only at the end of the calculations and that can be printed directly. For the researcher who develops tools, it is all well and good, but this is absolutely not recoverable academically. I see very bad for me to propose an article in a magazine showing that I am able to automatically integrate 3D pie charts in a PDF file. Of Indeed, the tools developed by researchers often simply outputs text, certainly comprehensive, but not presentable in the state reports to be disseminated widely. The outputs of R or Weka are a good example.

Tanagra, created by a teacher researcher, follows the same approach. Nothing was initially planned for the reporting. And yet, paradoxically, he suggested in one of its menus (DIAGRAM / CREATE REPORT) a tool for creating reports. This is the happy consequence of technology choice made when writing the specifications of the software.

Let's go back to understand the process. When I wrote SIPINA (version 3.x), I realized that the construction of the display windows of the results took me a lot of time, rather than writing algorithms for calculations. In my view, this was not a good thing because I am away from my main concern: to understand the methods, implement, evaluate, discuss. When I thought about the specifications of Tanagra, I thought it was absolutely necessary to define a display standardized necessarily with text output, but nevertheless have a relatively attrayante. Et là, j'ai redécouvert le HTML. C'est un peu amusant à dire, surtout en 2003. Le HTML permet de faire un effort minimum de description des sorties, une seule méthode dans la classe de calcul suffit (un peu comme Weka pour ceux qui sont allés voir le code source), tout en obtenant une présentation avenante. De plus, il est possible de mettre en évidence les informations importantes à lire en priorité. Par exemple, rien que pouvoir attribuer des codes couleurs à des tranches de p-value est infiniment précieux.

Par la suite, j'ai réalisé que le choix du HTML allait s'avérer doublement judicieux. En effet, c'est un standard largement répandu. Sans effort de programmation further, we can firstly get the output into an Excel spreadsheet on the other hand, we can export the display windows in an external file and view the results in a web browser, regardless of the software Tanagra. In fact, their distribution is greatly facilitated.

These are the features of "reporting" Tanagra we present in this tutorial.

Keywords: report, reporting, decision tree, C4.5, logistic regression, coding disjunctive, ROC curve, learning sample, test sample, variable selection
Components: GROUP CHARACTERIZATION, SAMPLING, C4.5, TEST, O_1_BINARIZE, FORWARD-LOGIT, BINARY LOGISTIC REGRESSION, SCORING, ROC CURVE
Tutorial: fr_Tanagra_Reporting.pdf
Data : heart disease

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naive Bayesian continuous predictors

The classifier Naive Bayes is a supervised learning method based on a strong simplifying assumption: the descriptors (Xj) are pairwise conditionally independent values of the variable to predict (Y). Yet despite this, it proves robust and efficient. Its performance is comparable to other learning techniques. Various reasons are advanced in the literature. We ourselves proposed an explanation based on bias of representation in a previous tutorial. When predictors are discrete, one realizes easily that the naive Bayesian classifier is a linear separator. It arises in direct competition with other techniques of the same ilk, such as discriminant analysis, logistic regression, SVM (Support Vector Machine) linear, etc..

In this tutorial, we describe the model of conditional independence within the framework of quantitative predictor variables. The situation is somewhat more complex. We shall see that the simplifying assumptions used, it can be considered as a linear or quadratic separator. It is then possible to produce a classifier explicit, easy to use for deployment. The ideas put forward in this tutorial have been implemented in Tanagra 1.4.37 (and later). This representation model is original. I have not found in other free software that I used to follow (for now ...).

This paper is organized as follows. Firstly (Section 2), we detail the theoretical aspects of the method. We show that it is possible to reach an explicit model that can be expressed as a linear combination of variables or variables of the square. In Section 3, we describe the implementation of the method using the software Tanagra. We compare the results with those of other separators linear (logistic regression, linear SVM, PLS discriminant analysis, discriminant analysis of Fisher). In Section 4, we compare the implementation of technology in various software. We will mainly focus on reading the results. Finally, Section 5, we show the usefulness of the approach on very large files. We will cover the basic "mutants" comprising 16,592 observations Predictors and 5408 with a speed beyond the reach of other techniques.

Keywords: Bayesian classifier naive model of conditional independence, 5.0.10 RapidMiner, Weka 3.7.2, 2.2.2 Knime, software R package e1071, discriminant analysis, PLS discriminant analysis, PLS regression, svm linear regression
Components: NAIVE BAYES CONTINUOUS, BINARY LOGISTIC REGRESSION, SVM, C-PLS, LINEAR DISCRIMINANT ANALYSIS
Tutorial: fr_Tanagra_Naive_Bayes_Continuous_Predictors.pdf
Data : breast ; Low Birth Weight
References:
Wikipedia, "Naive Bayes classification "
Tanagra, " Naïve Bayes classifier for discrete predictors "

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Tanagra - Version 1.4.37

Continuous Naive Bayes is a supervised learning component. It implements the model of conditional independence for continuous predictors (quantitative). The main originality lies in the production of an explicit model as a linear combination of predictor variables and, possibly, their square.

functionality reporting were improved.

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New interface for RapidMiner 5.0

La société Rapid-I, à travers leur logiciel phare RapidMiner, est un acteur très dynamique du l'informatique décisionnelle. Au-delà de l'outil, elle propose des solutions et des services dans le domaine de l'analyse prédictive, data mining et du text mining. Son site web regorge d'informations (blog, tutoriels, vidéos, forum, newsletter, wiki, etc.).

La version 5.0 de RapidMiner (Community Edition - Téléchargeable gratuitement) propose une interface profondément remaniée, s'inspirant visiblement de Knime. Les ressemblances entre les deux produits sont frappantes. Je me suis dit qu'il était opportun d'étudier cela en détail, evaluating its behavior in the context of a typical analysis. We hope to implement the following process: (1) construct and display a decision tree from a set of labeled observations, (2) save the tree in a file format PMML for later deployment and (3) assess the generalization performance of the classifier through cross-validation, (4) use the model to classify a set of unlabeled observations contained in a second file, the results (and label descriptors assigned) must be recorded in a third file in CSV format. These are

is very traditional tasks of data mining. We have repeatedly described in our courseware (eg SPAD ...). More reason to check it is easy to carry them out with this new version of RapidMiner. Indeed, with the previous version, some sequences were complicated. Establish a cross-validation, for example asking an organization, albeit a very rigorous in his mind, but not very intuitive.

Tags: RapidMiner, Knime, cross-validation, decision trees, deployment
Tutorial: fr_Tanagra_RapidMiner_5.pdf
Data : adult_rapidminer.zip
References:
Rapid-I, " RapidMiner "

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Call Prud'hommes. Get out there

We won! The layoffs are recognized "Without real and serious." We do not yet know the details for the damage (what the money!), But hey, it looks good! The scoop is that people in early retirement have also won (well, those who have complained!). Voilou! So, the collective struggles, it works! in this connection, it shows next Saturday!

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format PMML models for the deployment of Pentaho Data Integration

deployment models is a significant step in data mining. Under supervised learning, it is to make predictions by applying the models on unlabeled observations. We have repeatedly described the procedure for different tools (eg Tanagra, Sipina , Spad , or R). They have in common is to use the same software for the construction of the model and its deployment. This new tutorial

differ from earlier in that we use third party software for classifying new observations. It follows a remark made to me by LUCELLE Loïc (Loïc thank you very much for your valuable information), it made me realize two things: the deployment gave his full measure when it is realized with a tool dedicated to data management, we take the example of EC-PDI (Kettle), we reach a certain universality when we describe models using standards recognized / accepted by the majority of software, namely the PMML standard description.

I had already spoken several times to PMML. But so far, I do not see too much interest if we do not have a downstream tool capable of apprehending a generic way. In this tutorial we will see that it is possible to develop a decision tree with different tools (SIPINA, and KNIME RapidMiner), export PMML within standard, and deploy them indiscriminately on observations unlabeled via PDI-EC. Adopting a standard model description becomes particularly interesting in this case. Just

the margin of our discussion, we describe solutions deployment alternatives in this tutorial. We will see that Knime has its own interpreter PMML. It is capable of applying a model on new data, whatever the tool used for model development. The key is that the PMML standard is met. In this sense, Knime can substitute for PDI-EC. Another possible route, Weka, which is part of the suite "Pentaho Community Edition" has a description format owner directly recognized by PDI-EC.

Keywords: deployment, PMML, decision trees, 5.0.10 RapidMiner, Weka 3.7.2, Knime 2.1.1, 3.4 SIPINA
Tutorial: fr_Tanagra_PDI_Model_Deployment.pdf
Data : heart-pmml.zip
References:
Data Mining Group, "PMML standard "
Pentaho, " Pentaho Kettle Project "
Pentaho," Weka Scoring Using The Plugin "

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Business Intelligence (Business Intelligence - BI" in English, it is immediately more glamorous ) refers to "the exploitation of corporate data in order to facilitate decision-making. " Software suites propose to handle the entire process. I chose to put forward the following Pentaho Open Source, but the principles are valid for the vast majority of domain software.

There are two versions of Pentaho. The publishing company is paying, it provides access to assistance. I have not tested. The " Community Edition (CE Pentaho) can be downloaded freely. It is developed and maintained by a community of developers. I can not quite place differences between the two versions. For my part, I have focused on non-pay version, so that everyone can duplicate the operations that I describe.

This paper presents the implementation of Pentaho Data Integration Community Edition (PDI-EC, also called Kettle), the ETL Pentaho suite EC. I'm just a brief description for two reasons: this type of tool is not directly in my field of expertise (which is the data mining) and I speak especially to prepare for a next tutorial where I show the deployment models developed using Knime, Sipina or Weka via PDI-EC.

Keywords: ETL Pentaho Data Integration, Community Edition, kettle, data extraction, data import, food processing, businness intelligence, intelligence
Tutorial: PDI-EC
Data : titanic32x.csv.zip
References: How it
marche.net " Business Intelligence (BI) "
Pentaho, Pentaho Community

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Sipina Login / Excel via OLE [XL-SIPINA]

The connection between a data mining software and Excel (spreadsheets and more generally) is a major challenge. We had repeatedly addressed in our tutorials. Over time, the solution based on the use of add-ins (add-in) was imposed for both SIPINA que pour TANAGRA . Elle est simple, fiable, performante. Elle ne nécessite pas développer des versions spécifiques. La connexion avec Excel est une simple fonctionnalité additionnelle de la distribution standard.

Avant de parvenir à cette solution, nous avions exploré différentes pistes. Dans ce didacticiel, nous présentons la solution XL-SIPINA basée sur la technologie OLE de Microsoft. A contre-pied des macros complémentaires, cette version de SIPINA choisit d'intégrer Excel dans le logiciel de Data Mining. Le dispositif fonctionne plutôt bien. Néanmoins, il a finalement été abandonné pour deux raisons : (1) nous étions required to develop / compile special versions that only work if Excel is present on the user's machine, (2) the time of transfer "Excel object - Sipina" via OLE prove prohibitive when the database size increases .

must therefore be taken as a SIPINA XL-style exercise. There is always a bit of nostalgia when I look back on tracks that I explored and I finally abandoned. Maybe also I'm not completely gone after things.

last remark. The original application was developed using Office 97. I realize it is still relevant still, it works fine with Office 2010.

Keywords: excel, spreadsheet, SIPINA, xls, xlsx, xl SIPINA, decision trees
Software : XL- SIPINA
Tutorial: fr_xls_sipina.pdf
Data: cars

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The add-in for Excel 2007 Tanagra and 2010

The add ("add-in" in English) "tanagra.xla" contributes greatly to the spread of software Tanagra. The principle is simple, it involves integrating a menu in Excel Tanagra. Thus the user can launch the statistical calculations without having to leave the spreadsheet. Simple as it Regardless, this feature facilitates the work of the Data Miner. The spreadsheet is one of the most used tools for data preparation (see KDNuggets Polls: Tools / Languages for Data Cleaning - 2008 ). By integrating the data mining software in this environment, the practitioner avoids repetitive and tedious manipulations: import, export, check the compatibility of formats, etc..

Installing the add-in in Office XP (valid Office 1997 to Office 2003) is described in one of our tutorials . The procedure lapses in Office 2007 and Office 2010 since the menus of Excel were reorganized. Yet the macro will work. It is a shame that the users can not enjoy it.

In this tutorial, we detail the steps to follow to integrate the macro Tanagra in new versions of Excel. We will focus on Office 2007 in a first step, we see that the procedure is also valid for Office 2010. This transition to newer versions of Excel is absolutely not trivial. Indeed, compared to previous methods, they can manage a larger number of rows and columns. We can treat up to 1,048,575 base observations (the first line corresponds to the names of variables) et 16.384 variables .

Nous traiterons pour notre part une base comportant 100.000 observations et 22 variables. Il s'agit d'une version du fichier " waveform " bien connu des informaticiens. Notons que ce fichier, de par le nombre de lignes, ne peut pas être manipulé par les versions antérieures d'Excel.

La procédure décrite dans ce document est également valable pour la macro complémentaire associée au logiciel SIPINA ( sipina.xla ).

Mots-clés : importation des données, fichier excel, macro complémentaire, add-in, add-on, xls, xlsx
Composants : VIEW DATASET
Link: fr_Tanagra_Add_In_Excel_2007_2010.pdf
Data : wave100k.xlsx
References:
Tanagra, " Import XLS (Excel) - Add-.
Tanagra, "Connection Open Office Calc .
Tanagra, " Connecting Open Office Calc on Linux .
Tanagra, " Excel Connection - Sipina "

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Filtering predictors

The selection of variables is a crucial feature of supervised learning. It seeks to isolate the subset of predictors that permet d'expliquer efficacement les valeurs de la variable cible.

Trois approches sont généralement citées dans la littérature. Les méthodes " embedded " intègrent directement la sélection dans le processus d'apprentissage. Les méthodes " wrapper " optimisent explicitement un critère de précision, le plus souvent le taux d'erreur . Elles ne s'appuient en rien sur les caractéristiques de l'algorithme d'apprentissage qui est utilisé comme une boîte noire.

Enfin, troisième et dernière approche que nous étudierons dans ce didacticiel, les méthodes " filter " agissent en amont, avant la mise en implementation of the learning technique, and no direct connection with it. It is therefore assumed that an independent process based on an ad hoc criterion would identify relevant predictors regardless of the learning algorithm implemented downstream. The gamble is bold, even risky. And yet, some experiments show that the approach is viable even when the learning method used at the same time an integrated (embedded) selection of variables (decision trees with C4.5 for example).

We are interested in filtering methods (filter) based on the following principle: the subset of predictors selected should be composed of variables strongly associated with the target variable (relevance) but weakly related to each other (no redundancy) . Two ideas are to highlight in this pattern: (1) how to measure the association between variables, knowing that we restrict ourselves to the case of discrete predictors, (2) how to translate the redundancy in a subset of variables.

In this tutorial, we describe several methods of filtering based on a measure of correlation for discrete variables. We will apply a set of data that will be specially prepared for mettre en évidence leur comportement. Nous évaluerons alors leurs performances en construisant le modèle bayesien naïf à partir des sous-ensembles de variables sélectionnées. Nous mènerons l'expérimentation à l'aide du logiciel Tanagra ; par la suite, nous passerons en revue les méthodes filtres implémentées dans plusieurs logiciels libres de data mining ( Weka 3.6.0 , Orange 2.0b , RapidMiner 4.6.0 , R 2.9.2 - package FSelector ).

Mots clés : méthodes de filtrage, filter approach, correlation based measure, modèle bayesien naïf, modèle d'indépendance conditional
Components: FEATURE RANKING, CFS FILTERING, Miss FILTERING, FCBF FILTERING, MODTREE FILTERING, NAIVE BAYES, BOOTSTRAP
Link: fr_Tanagra_Filter_Method_Discrete_Predictors.pdf
Data: vote_filter_approach.zip
References:
R. Rakotomalala, Lallich S., " Construction of decision trees by optimization ", Journal of Knowledge Extraction and Learning, Vol. 16, No. 6 / 2002, pp.685-703, 2002.
Tutorial Tanagra, " STEPDISC - discriminant analysis"; " Strategy wrapper for selection variables ";" Wrapper for selection of variables (continued) "

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Discrete Data Mining under R - Package Deployment rattle

Tanagra's father is also a fan of R. It may seem strange and / or contradictory. But really, I'm mostly a big fan of data mining. And the software is an essential component. I spend so much time to dissect, evaluate their behavior in response to data, and analyze their source code where possible, in short, to study them in all seams. This work fascinates me altogether. I have always done. With the Internet, I can share the fruit of my reflections with others.

In this tutorial, we present the package to rattle R specializes in Data Mining. It does not include new methods of learning, but rather to add a graphical user interface (GUI in English, "graphical user interface") to R. Thus, a physician, unaware of the programming language R, will nevertheless drive its analysis by simply clicking on menus or buttons, just like the way "Explorer" software Weka. Nothing too revolutionary, then, but oh so important for novice users who want to go to basics: process their data using R without having to invest in learning the tedious programming.

To describe the operation of Rattle, we use the frame of the white paper published by its author in the Journal of R (see reference). We will achieve the following sequence of operations: load the file, split it into learning samples and testing, define the role of variables (target vs. Predictors) make some descriptive statistics and graphs to understand the data, build models predictors on the training sample, the gauge on the test sample through the usual tools of assessment (confusion matrix, a few curves).

Tags Key : R software, rpart, random forest, glm, decision trees, logistic regression, random forests, random forests
Link: fr_Tanagra_Rattle_Package_for_R.pdf
Data : heart_for_rattle.txt
References :
Togaware, "Rattle "
CRAN, "Rattle Package - Graphical user interface for data mining in R "
GJ Williams, " Rattle: A GUI for Data Mining R", R in The Journal Vol. 1 / 2, pages 45-55, december 2009.

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predictive models with R

Industrialization is the stage ultimate data mining. In the predictive framework, the goal is to classify an individual based on his description. It relies on the ability to save, distribute and operate the classifier developed during the learning phase in an operational environment. We talk about deployment.

In this tutorial, we present a deployment strategy for R. It rests on the ability to save templates in binary files via the package filehash . Admittedly, we still need the R software in the industrialization phase (for the classification of new individuals), but several aspects in favor of this strategy: R freely accessible and usable in any context whatsoever, it works equally well on Windows, Linux and MacOS (http://www.r-project.org/), we can control it in batch mode ie d . any program can call to R in hand under him to execute a task, and retrieve results.

We will write three separate programs to differentiate the stages. The first models built from training data and stores it in a binary file. The second load models and used to classify individuals of a second unlabeled data set. The predictions are saved in a CSV file. The third load predictions and the true class membership stored in a third file, it builds the confusion matrices and calculates the error rate. Data mining methods are used: decision trees (rpart ) logistic regression (glm ) linear discriminant analysis (lda ) and discriminant analysis on factors of the PCA ( princomp + lda ). With the latter case, we show that the strategy remains operational even when the prediction requires a sequence of complex operations.

Keywords : R software, deployment, industrialization, rpart, lda, pca, glm, decision trees, discriminant analysis, logistic regression, principal components analysis, discriminant analysis on factors
Link: fr_Tanagra_Deploying_Predictive_Models_with_R.pdf
Data : Pima-model-deployment.zip
References:
R package, " Filehash: Simple key-value database "
Kdnuggets, "Data mining deployment Poll "

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treatment of very large files with R

The treatment of large files is a recurring problem of data mining. In this tutorial, we will investigate a solution implemented in R as a bookseller. The package "filehash" allows you to copy (the "dumper" altogether) all kinds of items on the disc, but also data models. It uses a standard format database. It has a huge advantage, it is possible to use standard statistical functions or from other packages without having to make any adjustment. Instead manipulating data frame in memory, they work on the data frame stored on the disk, seamlessly. It's pretty amazing, I must admit. Processing capabilities are greatly improved and At the same time, the degradation of the computing time is not prohibitive.

Nevertheless, we find that the R functions not specifically designed for the apprehension of large data sets, even when we increase our demands, the calculations are not possible when resources are not fully utilized. It's a bit generic approaches the limit. Modification of learning algorithms is often necessary to exploit the particularities of context. It should even go further. To get results really convincing, it would both adapt the learning algorithms and accordingly organize data on disk. A solution that would suit any type of analysis is difficult, even illusory.

To evaluate the solution provided by the package "filehash" We study the computational time and memory usage, with or without swapping to disk during the calculation of descriptive statistics, the induction of a tree decision with rpart package of the same name, and modeling using discriminant analysis with function lda of the MASS library.

We will achieve the same operations in SIPINA. Indeed, it also offers a solution to swap the apprehension of very large databases. We can compare the performance of strategies implemented.

Keywords: high-volume, very large files, large databases, decision tree, discriminant analysis, SIPINA, C4.5, rpart, lda
Link: fr_Tanagra_Dealing_Very_Large_Dataset_With_R.pdf
Data : wave2M.txt.zip
References:
R package, " Filehash: Simple key-value database "
Tutorial Tanagra, " processing large volumes - Comparison of software "
Tutorial Tanagra, " Sipina - Treatment of very large files "
Yu-Sung Su's Blog, " Dealing with large dataset in R "

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Modulad Tanagra in Review (2005)

Still on nostalgia, spring cleaning lends itself much the exhumation of old documents, I found the long version of the article EGC Modulad published in the journal (No. 32-2005).

Review Modulad combines the benefits. It is this long ago, sustainability is often a sign of quality. It is in French. They are not numerous in our area. And (especially I'd be tempted to say), it is freely accessible online. So we can access articles very interesting, since recent or older archives are available. The number 1 in 1988. The old documents have been scanned.

Another very pleasant, with the page Excel'ense , we have lots of tutorials describing the statistical data in a spreadsheet. The examples show, if needed, that the spreadsheet is very much a place among the statistical software. We can achieve many treatments just by using the common functions.

Article: Tanagra - Journal Modulad
Reference: R. Rakotomalala, "Tanagra, an experimental platform for data mining", Journal Modulad, No. 32, pp. 70-85, 2005.

O Holy Night Michael Burgess

Voltaire liquidation

The Bedding Voltaire (MKB sign distribution, represented by Jean-Jacques Ben Harrous) was placed in

liquidation

since January 28 2010,

date of commencement of liquidation proceedings.

URGENT

All creditors should apply without delay in writing to the CPS Brouard-Daude (34, rue Sainte-Anne 75001, Paris).

In the person of Xavier Brouard, liquidator. D years in the mail to send RAR, specifically relate the facts.

Tel. 01 40 20 92 60.

To file a complaint, it must write

Attorney Republic

14, quai des Louvres goldsmiths 75059 Paris SP RP

can also go there: the complaint is recorded immediately.

In mail RAR must relate the facts accurately and clearly, the conditions of purchase and payment. Specify that the purchase was made after the liquidation. It is also necessary to question the person who was in the shop. Do not forget to say that other people are in the same situation.

Several procedures are underway. Complaints have already been filed.

All company information is public and verifiable on the site Infogreffe Tribunal of Paris and the Paris Tribunal.

Where threats from the Bedding Voltaire, a complaint must be lodged at the police immediately. It would also be good if the liquidator is promptly informed.

Tip of the Day! : contact brand of bed you've chosen and report their behavior to the family Ben Harrous. They may be held liable if they continue to do business with them.

The news of the day! a new complaint has been filed (June 1, 2010) with the prosecutor against the Ben Harrous.

Harrous If Ben does not pay, it could end badly for them. The group created this blog is very determined to go through.

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Scam Bedding Voltaire but who is Ben Yohan Harrous? The scam

You met the bedding Voltaire Yohan Harrous Ben, you were not well received and defrauded. Want to know more? This blog is for you. This character

little creep who lives 13, avenue Claude Monnet Annet sur Marne (77 410, tel. 09 63 51 11 24) in a fine flag which this is the photo


is the manager of a company founded on August 3, 2009 . This company called

Decor and nuance

whose headquarters

4 boulevard Faraday, 77700 Serris.

01 60 42 87 87

01 60 42 87 97

fax 01 60 42 87 80

reviews of this company, you now know what you may ...

Yohan Harrous Ben is the son of

Jean-Jacques Ben Harrous .

It inhabits

13 Villa Curial 75019 Paris

Nadia Bjorlin Piercing

bedding Voltaire in Paris

Hello,

You too have been scammed by bedding Voltaire in Paris?

( 20 Rue Godefroy Cavaignac 75011 Paris)

You have been trapped by the false promotions website literievoltaire.fr ?

You phoned dozens of times in vain?

There is also the same company on the Internet under the name Best Bedding . Your testimony

interest.

We must condemn the actions of these rogue traders who promised deliveries that never arrive. These are people who lie just scrupulously to their customers and try to have them wear.

The shop where you faced called Yohan Ben Harrous , descending course of the founders of the company Marianne Ben Harrous and Jean-Jacques Ben Harrous question.

Yohan Harrous Ben is the one who calls himself Mr. Voltaire.

Yohan Harrous Ben is the one who continues to lie about delivery time of a delivery that never came.

Yohan Harrous Ben is the one who insults you when you call to get your money back.

Yohan Ben Harrous course YOBH person who signs (of cause will YO Han B in Arrous H) or Youb when making hoax messages to extol the merits Voltaire bedding on the Internet.

Write here your unfortunate experience. Do not stay alone. Unity is strength.

Feel free to file a complaint against the company.

Attention Best Bedding site belongs to the same company, as well as bedding Vaugirard.

Here is a copy of messages of complaint I could find on the Internet:

On the e-Komerco:

macelinepivoine , April 22, 2010 on the site Merchant Bedding online Voltaire [ www.literievoltaire.fr ]
Warning bedding voltaire see no serious dishonest. 4X purchase a mattress with immediate first deposit by credit card. 6 weeks for your order! 2 calls per week to be told she was gone. To date, three payments were received, eight weeks have passed and still no news of the delivery which should be provided within 48 hours of receipt of this product to my chèques.Plus possible to backtrack. Two options: wait or make a complaint.

sharkos , le 23 avril 2010 sur le site marchand Literie en ligne Voltaire [ www.literievoltaire.fr ]
ATTENTION ! Ce vendeur est plus que mauvais cela fait 2 Mois que j'ai commander un ensemble matelas sommier sur leur site! et toujours rien ! après de nombreux appel (je ne les comptent plus!)A chaque fois le même refrain ! "ça vas arriver la semaine prochaine " mais en attendant toujours rien ... jusqu'au moment ou j'ai due encore téléphoner et la on m'a dit "c'est chez le transporteur !" due coup j'appel le transporteur qui me répond "oui mais c'est pas nous qui nous en occupons vue que you are in the province! "And since still no news! Carrier unreachable and the shop! Really Fuyer this site and this shop!

On the Qype site:

April 22, 2010

Bedding Voltaire worth avoiding.
Dishonest see scam check.
8 weeks we expect a mattress and promised to pay by credit card within 48 hours. 6 weeks to get a receipt in lieu of bill despite regular phone calls during which there was agreement that the party had received "yesterday".'s homepage on the phone is charming with the order, the website announced the best deals, articles and livraiisons available in 48 hours. The reality is quite different. What solution now?

April 23, 2010

SITE not serious at all! it's been two months I've waited for my order! and still nothing on the phone people are more than unpleasant! and extremely difficult to have! frankly do not buy anything on their site or even in stores!

May 4, 2010

WARNING: this seller is a crook. Go your way or you may find yourself with no bed and no money. Delivery times are not required and the goods never delivered. For customers who are obviously not delivered many, you should seek immediate repayment of amounts paid. Do not hesitate to refer the matter to court. Such traders do not deserve to work.

Attention, a satisfied customer claimed the name comes Yobh here and there to say how much he thinks of the sign. It's the same person and what are the initials Yohan Ben Harrous. Of course, this is pure disinformation.