Random Forest Predictor

Predicts patterns according to an aggregation of the predictions of the individual trees in a random forest* model.

(*) RANDOM FORESTS is a registered trademark of Minitab, LLC and is used with Minitab’s permission.

Options

Change prediction column name
Select if you want to change the name of the column containing the prediction.
Prediction column name
The name of the column that will contain the prediction of the tree ensemble model
Append overall prediction confidence
The confidence of the predicted class. It is the maximum of all confidence values (which can be appended separately).
Append individual class probabilities
For each class the prediction confidence. It's the number of trees predicting to the current class (as per column name) divided by the total number of trees.
Suffix for probability columns
Here a suffix for the names of the class probability columns can be entered.
Use soft voting
Per default ("hard voting") the class that receives the most votes is predicted. In case of "soft voting" the class probabilities of all trees are aggregated and the class with the highest aggregated probability is predicted. In order for this to work properly, the random forest model needs to contain the class distributions. This can be specified in the learner node by selecting the option "Save target distribution in tree nodes". Setting this option on models that do not have the target distributions saved, will cause a warning message to be issued.

Input Ports

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The output of the learner.
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Data to be predicted.

Output Ports

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Input data along with prediction columns.

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Installation

To use this node in KNIME, install the extension KNIME Ensemble Learning Wrappers from the below update site following our NodePit Product and Node Installation Guide:

v5.3

A zipped version of the software site can be downloaded here.

Plugin provider: KNIME AG, Zurich, Switzerland
Plugin version: 5.3.0.v202401171201
On NodePit since: 2024-07-09
Last update: 2024-11-21
Tags: Streamable
KNIME versions: Since v3.6

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