The following node is available in the Open Source KNIME predictive analytics and data mining platform version 2.7.1. Discover over 1000 other nodes, as well as enterprise functionality at http://knime.com.

Lift Chart

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.

Dialog Options

Column containing true labels
Nominal column containing the actual labels, e. g. if a person responded
Response Label
The label for a positive value (hit).
Column containing score (probabilities)
Numeric column containing the predicted score in probabilities of the model
Interval width in %
The width in which the data is separated before counting.

Ports

Input Ports
0 Data table
Output Ports
0 Data table sorted by probability

Views

Lift Chart
The lift chart
This node is contained in KNIME Base Nodes provided by KNIME GmbH, Konstanz, Germany.