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Decision Tree Predictor
KNIME Base Nodes version 4.3.1.v202101261649 by KNIME AG, Zurich, Switzerland
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 HiLite
- 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.
- Prediction Column
- The possibly overridden column name for the predicted column. (The
default is:
Prediction (trainingColumn).) - Append columns with normalized class distribution
- Shows the normalized class distribution for each prediction.
- Suffix for probability columns
- Suffix for the normalized distribution columns. Their names are like:
P (trainingColumn=value).
Input Ports
Output Ports
- The input table with one column added containing the classification and the probabilities depending on the options
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.
Best Friends (Incoming)
- Decision Tree Learner (50 %)
- Partitioning (19 %)
- X-Partitioner (3 %)
- Color Appender (2 %)
- Column Filter (2 %) Streamable
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Best Friends (Outgoing)
- X-Aggregator (13 %)
- Joiner (9 %)
- Scorer (7 %)
- Column Filter (5 %) Streamable
- ROC Curve (local) (5 %)
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Workflows
00_Random_Forest_knimepy (KNIME Hub) - 01_Analytics (KNIME Hub)
- 01_AutoML_Component_via_Interactive_Views (KNIME Hub)
- 01_B2B_Customer_Analytics (KNIME Hub)
- 01_Bike_Restocking_Alert_Training_w_Feature_Selection (KNIME Hub)
- Show all 241 workflows
Installation
To use this node in KNIME, install KNIME Base nodes from the following update site:
KNIME 4.3
A zipped version of the software site can be downloaded here.
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Developers
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