This node uses a SVM model generated by the SVM learner node to predict the output for given values. Only the columns that have been used during training are used in the SVM learner. The output table will contain one extra column, which contains the prediction and optinally the class probabilities.
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- Column Filter5 %
- Scorer (JavaScript)3 %
String To Number2 %- Numeric Scorer1 %
- Math Formula1 %
- Table View (JavaScript)1 %
Scorer< 1 %Number To String< 1 %- ROC Curve< 1 %
- ROC Curve (JavaScript)< 1 %
- CSV Writer< 1 %
- Joiner< 1 %
Excel Writer (XLS)< 1 %- Bar Chart< 1 %
- Decision Tree Predictor< 1 %
Linear Correlation< 1 %- Missing Value Column Filter< 1 %
- RowID< 1 %
- Capture Workflow End< 1 %
- Voting Loop End< 1 %
- Loop End< 1 %
- SVM Predictor< 1 %
- String to Number< 1 %
Row Filter (deprecated)< 1 %- Lift Chart (JavaScript)< 1 %
- Data to Report (BIRT)< 1 %
- X-Partitioner< 1 %
Naive Bayes Learner< 1 %- SVM Learner< 1 %
- Category to Number< 1 %
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- Pie Chart< 1 %
- Boosting Learner Loop End< 1 %
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- MultiLayerPerceptron Predictor< 1 %
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Excel Sheet Appender (XLS)< 1 %- Radar Plot Appender< 1 %
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Python Script (2⇒2)< 1 %- Python View (legacy)< 1 %
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Active Learn Loop End< 1 %PBAC Scorer< 1 %Table Column to Variable< 1 %- Table Row to Variable< 1 %
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CSV Writer< 1 %Database Writer< 1 %Table Writer< 1 %Backward Feature Elimination End< 1 %Backward Feature Elimination Start (1:1)< 1 %- Feature Selection Loop Start (1:1)< 1 %
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- Random Forest Predictor< 1 %
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Column Appender< 1 %- One to Many< 1 %
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- Correlation Filter< 1 %
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Python Script (1⇒1)< 1 %Python Script (1⇒1)< 1 %- Modify Date< 1 %
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Workflows
Credit Scoring Model(diksha kumari)KNIME Hub- (test) credit score modelKNIME Hub
- 01_Combining_Classifiers_using_Prediction_FusionKNIME Hub
- 01_CreditScoringKNIME Hub
- 01_CreditScoringKNIME Hub
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