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
Output Ports
- Results of classification with probability attribution for each class
- Group diagnostic for numerical variables (mean by groups of entry variables)
- Group diagnostic for categorical variables (crosstab and Cell Chi² between classication variable and each categorical variable in the entry set)
- Points coordinates resulting from AFMD
- SQL generated instructions
- Confusion matrix between the QualClassif process and sql instructions
- Diagnose sql versus QualClassif
Nodes
Extensions
- FeatureKNIME Base nodes
- FeatureKNIME Data Generation
- FeatureKNIME JavaScript Views
- FeatureKNIME Javasnippet
- FeatureKNIME Math Expression (JEP)
- FeatureKNIME PMML Translation
- FeatureKNIME Quick Forms
- FeatureKNIME Weka Data Mining Integration (3.7)
Links
- No links available