This node takes a model built with a feature selection loop as input and lets you choose the subset of columns you want to include in the output table. The dialog shows all computed subsets together with their scores. You can select a subset manually or specify a score threshold. If you specify a threshold, the smallest features set whose score meets the threshold requirement is selected. If the "Minimize Score" option was checked in the Feature Selection Loop End node, this is the smallest feature set with a score below the specified threshold; if the "Minimize Score" option was left unchecked in the Feature Selection Loop End node, this is the smallest feature set with a score above the specified threshold.
Options
Popular Predecessors
- Feature Selection Loop End33 %
CSV Reader4 %- CSV Reader4 %
- Column Filter4 %
- Feature Selection Loop Start (1:1)4 %
- Number to String3 %
Scorer3 %- Partitioning3 %
Linear Correlation2 %- Normalizer2 %
- Numeric Scorer2 %
- Scorer2 %
Table Row to Variable2 %- Correlation Filter1 %
File Reader1 %Number To String1 %Excel Reader (XLS)< 1 %- Rule Engine< 1 %
Model Reader< 1 %- Numeric Outliers< 1 %
Excel Reader (XLS)< 1 %- One to Many< 1 %
- Missing Value< 1 %
- Feature Selection Filter< 1 %
- Color Manager< 1 %
- Model Reader< 1 %
- Math Formula< 1 %
- GroupBy< 1 %
- Excel Reader< 1 %
- ROC Curve (legacy)< 1 %
- Missing Value Column Filter< 1 %
- Row Filter< 1 %
- Rule-based Row Filter< 1 %
Table Column to Variable< 1 %- ARFF Reader< 1 %
- Feature Selection Loop Start (2:2)< 1 %
- Linear Regression Learner< 1 %
Table Row to Variable< 1 %- Random Forest Learner< 1 %
- Sorter< 1 %
- Joiner< 1 %
- Equal Size Sampling< 1 %
- Parameter Optimization Loop Start< 1 %
- R Snippet< 1 %
Column Appender< 1 %- Normalizer (Apply)< 1 %
- X-Partitioner< 1 %
- Concatenate< 1 %
- Statistics< 1 %
- File Reader< 1 %
- String to Number< 1 %
- SMOTE< 1 %
- Domain Calculator< 1 %
- Math Formula (Variable)< 1 %
- k-Means< 1 %
- Regression Predictor< 1 %
- Random Forest Predictor< 1 %
- Rank Correlation< 1 %
- Table Row to Variable< 1 %
- Decision Tree Predictor< 1 %
- Logistic Regression Predictor< 1 %
- Row Sampling< 1 %
- Column Splitter< 1 %
- Data Explorer< 1 %
- Linear Correlation< 1 %
- Column Appender< 1 %
Naive Bayes Predictor< 1 %String To Number< 1 %Column Rename< 1 %- Constant Value Column Filter< 1 %
- Create Collection Column< 1 %
- Table Column to Variable< 1 %
Table Reader< 1 %Cell Replacer< 1 %- Shuffle< 1 %
- H2O to Table< 1 %
- Rule Engine Variable< 1 %
- Parameter Optimization Loop End< 1 %
- Auto-Binner (Apply)< 1 %
- Constant Value Column< 1 %
- Column Expressions< 1 %
Counting Loop Start< 1 %Random Forest Predictor< 1 %- Low Variance Filter< 1 %
- Data Generator< 1 %
- Cell to Model< 1 %
- Integer Input (legacy)< 1 %
Numeric Scorer< 1 %- SVM Predictor< 1 %
- Random Forest Predictor (Regression)< 1 %
- Bootstrap Sampling< 1 %
- Category to Number< 1 %
- Cross Joiner< 1 %
- Denormalizer< 1 %
- Column Filter (PMML)< 1 %
- Normalizer Apply (PMML)< 1 %
- Rule-based Row Splitter< 1 %
- Extract Table Spec< 1 %
Variable to Table Column< 1 %Table Row To Variable Loop Start< 1 %PCA< 1 %Concatenate (Optional in)< 1 %- Column Renamer (Dictionary)< 1 %
- Column Resorter< 1 %
- Reference Column Filter< 1 %
- Nominal Value Row Filter< 1 %
Joiner< 1 %Rank Correlation< 1 %- Line Plot (legacy)< 1 %
- Parallel Coordinates Plot (JavaScript)< 1 %
- Multiple Selections (legacy)< 1 %
- Inverter< 1 %
- Table Row To Variable Run-for-time Loop Start< 1 %
- Wait...< 1 %
- Extract Variables (Data)< 1 %
- Read Images< 1 %
Database Reader< 1 %- Table Creator< 1 %
Backward Feature Elimination End< 1 %Loop End< 1 %- X-Aggregator< 1 %
Naive Bayes Learner< 1 %- Fuzzy c-Means< 1 %
- DBSCAN< 1 %
- K Nearest Neighbor< 1 %
- Logistic Regression Learner< 1 %
- Entropy Scorer< 1 %
- Random Forest Learner (Regression)< 1 %
- Simple Regression Tree Predictor< 1 %
- Auto-Binner< 1 %
- Cell Splitter By Position< 1 %
- Column Auto Type Cast< 1 %
- Column Name Extractor< 1 %
- Column Merger< 1 %
- Double to Integer< 1 %
- Row Splitter< 1 %
- Pivot< 1 %
- One to Many (PMML)< 1 %
- Missing Value (Apply)< 1 %
- Normalizer (PMML)< 1 %
- Numeric Row Splitter< 1 %
- String Manipulation< 1 %
String Replace (Dictionary)< 1 %- Table Transposer< 1 %
- One-way ANOVA< 1 %
- Timer Info< 1 %
- Parallel Chunk Start< 1 %
- H2O Generalized Linear Model Learner (Regression)< 1 %
- Math Formula (Multi Column)< 1 %
- Multiple Selection Configuration< 1 %
- Value Filter (legacy)< 1 %
- Single Selection (legacy)< 1 %
- Line Plot (JavaScript)< 1 %
- R Source (Table)< 1 %
- Table Row to Variable Loop Start< 1 %
- Naive Bayes Learner< 1 %
- Fuzzy Rule Learner< 1 %
- Fuzzy Rule Predictor< 1 %
- Polynomial Regression Learner< 1 %
- PCA< 1 %
- Gradient Boosted Trees Predictor< 1 %
- Column Aggregator< 1 %
- Duplicate Row Filter< 1 %
- Table Manipulator< 1 %
- String to Number (PMML)< 1 %
CASE Switch Model (End)< 1 %- IF Switch< 1 %
CASE Switch Data (Start)< 1 %- DB Query Reader< 1 %
- Model Loop Start< 1 %
- Category to Class< 1 %
- String to Path (Variable)< 1 %
- Column Selection Configuration< 1 %
- Column Selection (legacy)< 1 %
- ROC Curve (JavaScript)< 1 %
- Scatter Plot (JavaScript)< 1 %
- Integer Widget< 1 %
- Column Selection Widget< 1 %
- Moving Aggregator< 1 %
- String to Date/Time (legacy)< 1 %
Views
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Workflows
01_AnalyticsKNIME Hub- 01_AnalyticsKNIME Hub
- 01_Bike_Restocking_Alert_Training_w_Feature_SelectionKNIME Hub
- 01_Feature_Elimination_Done_ManuallyKNIME Hub
- 01_Feature_Elimination_with_Naive_BayesKNIME Hub
- Show all 127 workflows
Links
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Developers
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