Logistic Regression Predictor

Predicts the response using a logistic regression model. The node needs to be connected to a logistic regression node model and some test data. It is only executable if the test data contains the columns that are used by the learner model. This node appends a new columns to the input table containing the prediction for each row.

Options

Custom prediction column name

Allows you to specify a customized name for the prediction column that is appended to the input table. If not checked, "Prediction (target)" (where target is the name of the target column of the provided regression model) is used as default.

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.

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Links

• KNIME E-Learning Course: Logistic Regression

  www.knime.com/knime-introductory-course/chapter6/section2/logistic-regression

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