Decision Tree Predictor

This node uses an existing decision tree (passed in through the model port) to predict the class value for new patterns. The Node can be configured as follows:

Options

Number of patterns for hiliting
Determines the maximum number of patterns the tree will store to support hiliting.
Change prediction column name
When set, you can change the name of the prediction column. The default prediction column name is: Prediction (trainingColumn).
Append columns with normalized class distribution
If selected, a column is appended for each class instance with the normalized probability of this row being a member of this class. The probability columns will have names like: P (trainingColumn=value) with an optional suffix that can be specified.

Input Ports

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A previously learned decision tree model.
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Input data to classify.

Output Ports

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The input table with one column added containing the classification and the probabilities depending on the options.

Popular Predecessors

Views

Decision Tree View
The decision tree as given in the model port along with the classified data. The tree can be expanded and collapsed with the plus/minus signs.
Decision Tree View (simple)
The decision tree as given in the model port along with the classified data.

Workflows

Links

Developers

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