Lift Chart

Visualizer

Creates a lift chart. Additionally, a chart for the cumulative percent of responses captured is shown. A lift chart is used to evaluate a predictive model. The higher the lift (the difference between the "lift" line and the base line), the better performs the predictive model. The lift is the ratio between the results obtained with and without the predictive model. It is calculated as number of positive hits (e .g. responses) divided by the average number of positives without model. The data table must have a column containing probabilities and a nominal column, containing the actual labels. At first, the data is sorted by probability, divided into deciles, then the actual labels are counted and the average rate is calculated.

Input Ports

  1. Type: Data Data table

Output Ports

  1. Type: Data Data table sorted by probability

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KNIME Core

Update site for KNIME Analytics Platform 3.7:
KNIME Analytics Platform 3.7 Update Site

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