Similarity Measure

Use the drop-down menu to select the similarity measure to be used for optimizing the predictor set.

Available options are described in the table below:

Option	Definition
Pearson Correlation	Choose this option to compute a parametric measure of association for each pair of variables. See Pearson Product-Moment Correlation for more information.
Hoeffding Correlation	Choose this option to compute a a nonparametric measure of association that detects more general departures from independence. See Hoeffding Dependence Coefficient for more information.
Kendall Correlation	Choose this option to compute a nonparametric measure of association based on the number of concordances and discordances in paired observations. See Kendall’s Tau-b Correlation Coefficient for more information.
Spearman Correlation	Choose this option to compute a nonparametric measure of association based on the ranks of the data values. See Spearman Rank-Order Correlation for more information.

To Specify the Similarity Measure:

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Make sure that the Optimize the continuous predictor set check box is checked.

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Select the desired measure using the drop-down menu.