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SPAD7 Data Miner Guide.pdf

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22 quai gallieni - 92150 Suresnes - France Tél : +33 1 57 32 60 60 - Fax : +33 1 57 32 62 00 spad@coheris.com – www.coheris.com Siret : 399 467 927 00105 - APE : 5829C Register number training: 11-92-1522492 DATA MINER GUIDE Descriptive St
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    22 quai gallieni - 92150 Suresnes - France  Tél : +33 1 57 32 60 60  - Fax : +33 1 57  32 62 00 spad@ coheris . com  – www. coheris . com  Siret : 399   467   927  00 105  - APE : 5829C   Register number training : 11- 92 - 1522492   D ATA M INER G UIDE    Descriptive Statistics - Factorial Analyses - Clustering  Linear Models – Discriminant Analyses – Scoring – Decision Trees    Tél : +33 1 57 32 60 60  - Fax : +33 1 57 32 62 00  www. coheris . com  Siret : 399   467   927  00 105  - APE : 5829C   Register number training  : 11- 92 - 1522492   Data Miner Guide © Copyright 1996, 2008 SPAD. All rights reserved. For any further information about the SPAD software, training and consulting activities, please visit us at www. coheris.com  or contact us by email: About E-mail SPAD Software info -spad @ coheris.com  SPAD Hot line support -spad @ coheris . com  Training formation -spad @ coheris . com  Consulting consulting -spad @ coheris . com  Books publication -spad @ coheris . com   For further information about the COHERIS Group offer (CRM, BI, Data Mining, Data Quality  Management, Merchandising Sfa), visit us at www.coheris.com   3 Table of contents D ESCRIPTIVE S TATISTICS WITH SPAD 4   STATS   -  MARGINAL DISTRIBUTIONS ,   H ISTOGRAMS  5   DEMOD   –   A UTOMATIC C HARACTERIZATION OF A QUALITATIVE VARIABLE  16   DESCO   -   A UTOMATIC C HARACTERIZATION OF A CONTINUOUS VARIABLE  21   TABLE   -   C ROSS TABLES  25   BIVAR   -   B IVARIATE A NALYSIS  28   F ACTORIAL A NALYSES WITH SPAD 30   PCA   -   P RINCIPAL C OMPONENT A NALYSIS  32   SCA   -   S IMPLE CORRESPONDENCE ANALYSIS  45   MCA   -   M ULTIPLE C ORRESPONDENCE A NALYSIS  50   C LUSTERING WITH SPAD 62   RECIP    /    SEMIS   -   C LUSTERING ON FACTORS SCORES  63   PARTI   -   DECLA   -   C UT OF THE TREE AND CLUSTERS DESCRIPTION  69   CLASS   -   MINER   -   C LUSTERS DESCRIPTION  78   ESCAL   -   S TORING THE FACTORIAL AXES AND THE PARTITIONS  79   T HE L INEAR M ODEL AND ITS APPLICATIONS  80   R EGRESSION AND A NALYSIS OF V ARIABCE ,   G ENERAL L INEAR M ODEL  80   O PTIMAL R EGRESSIONS R ESEARCH  85   L OGISTIC R EGRESSION  94   T HE D ISCRIMINANT AND ITS METHODS  105   FUWILD   -   O PTIMAL D ISCRIMINANT A NALYSIS  105   DIS2GD   -   L INEAR D ISCRIMINANT A NALYSIS BASED ON CONTINUOUS VARIABLES  117   DIS2GFP   -   L INEAR D ISCRIMINANT A NALYSIS BASED ON P RINCIPAL F ACTORS  126   DISCO   -   D ISCRIMINANT A NALYSIS BASED ON Q UALITATIVE VARIABLES  134   SCORE   -   S CORING F UNCTION  134   IDT   1   -   I NTERACTIVE D ECISION T REE 1 154   IDT   2   -   I NTERACTIVE D ECISION T REE 2 154      4 D ESCRIPTIVE S TATISTICS WITH SPAD STATS  : marginal distributions, histograms, matrix plot, box plot DEMOD  : automatic characterization of a qualitative variable DESCO  : automatic characterization of a continuous variable TABLE  : Crossed tables BIVAR  : Bivariate analysis

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Jul 23, 2017

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Jul 23, 2017
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