QualClassif

Complete classification admitting numerical and categorical variables in entry. Perform AFMD then Xmeans and logistic regression in the end to validate the Xmeans results and reprocess the classification.

Generate sql instructions in order to reproduce the classification in a most automatized way directly from the orginal datas.

Warning : use Weka 3.7 components

Options

Columns selection
Columns selection
Minimm number of elements by node for tree sql generation
Minimm number of elements by node for tree sql generation
Minimum number of clusters
Minimum number of clusters
Maximum number of clusters
Maximum number of clusters

Input Ports

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Entry table

Output Ports

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Results of classification with probability attribution for each class
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Group diagnostic for numerical variables (mean by groups of entry variables)
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Group diagnostic for categorical variables (crosstab and Cell Chi² between classication variable and each categorical variable in the entry set)
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Points coordinates resulting from AFMD
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SQL generated instructions
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Confusion matrix between the QualClassif process and sql instructions
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Diagnose sql versus QualClassif

Nodes

Extensions

Links