This is the start node of a backward feature elimination loop. The first iteration of the loop is executed
with all input columns. In the next
n - 1
iterations each of the input columns - except the target column, that must be selected in the dialog - is
left out once. Then the end node will discard the column that influenced the prediction result the least.
Then
n - 2
iterations follow where each of the remaining columns is left out once, and so on. The total number of
iterations is therefore
n * (n + 1) / 2 - 1.
The backward feature elimination loop can handle arbitrary target column, for numerical columns the squared
error is taken as quality measure, for all other columns the error rate (i.e. the fraction of rows for which
target and prediction column have different values).
Popular Successors
- Partitioning39 %
Backward Feature Elimination End19 %- X-Partitioner6 %
Backward Feature Elimination Filter6 %Backward Feature Elimination Start (2:2)4 %- Decision Tree Learner4 %
Naive Bayes Learner3 %Logistic Regression Learner2 %- Linear Regression Learner2 %
- Weka Predictor (3.7)2 %
- Polynomial Regression Learner1 %
Backward Feature Elimination Start (1:1)< 1 %- Logistic Regression Learner< 1 %
- Interactive Table (legacy)< 1 %
- RProp MLP Learner< 1 %
PCA< 1 %- Logistic Regression Predictor< 1 %
Random Forest Learner< 1 %- Random Forest Learner (Regression)< 1 %
- Normalizer< 1 %
- ARIMA Learner< 1 %
- PNN Learner (DDA)< 1 %
Decision Tree Learner< 1 %Scorer< 1 %- SVM Learner< 1 %
Random Forest Learner (Regression)< 1 %Gradient Boosted Trees Learner< 1 %Gradient Boosted Trees Learner (Regression)< 1 %Linear Correlation< 1 %- Low Variance Filter< 1 %
- Missing Value< 1 %
- Rule-based Row Splitter< 1 %
- ROC Curve (legacy)< 1 %
- ARFF Writer< 1 %
CSV Writer< 1 %Naive Bayes Learner< 1 %- PNN Predictor< 1 %
- Hierarchical Clustering< 1 %
- k-Means< 1 %
- Decision Tree Predictor< 1 %
Regression Predictor< 1 %Tree Ensemble Learner< 1 %Tree Ensemble Learner< 1 %Random Forest Learner< 1 %Random Forest Predictor< 1 %- Simple Regression Tree Learner< 1 %
- Create Bit Vector< 1 %
- Column Filter< 1 %
Row Splitter (deprecated)< 1 %- Rule Engine< 1 %
- Statistics< 1 %
- R Snippet< 1 %
Views
- This node has no views
Workflows
- No workflows found
Links
- No links available
Developers
You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.