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GeneXproTools Online Guide

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Last update: February 19, 2014

 

Variable Importance

GeneXproTools uses a sophisticated stochastic method to compute the variable importance of all the variables in a model. For all kinds of models (classification, logistic regression, regression, time series prediction and logic synthesis) and for all datasets, the importance of each model variable is computed by randomizing its input values and then computing the decrease in the R-square between the model output and the target. The results for all variables are then normalized so that they add up to 1.

GeneXproTools evaluates the variable importance of all the variables (original and derived) in a model and shows the results in the Statistics Report in the Data Panel. The variable importance is also shown graphically in the Variable Importance Chart in the Data Panel.



The Variable Importance Chart is available through the Statistics Charts in the Data Panel. By selecting Model Variables in the Variables combobox, you can quickly access the variables of each model and quickly visualize their relative importance in a chart. The variable importance is computed for all the models GeneXproTools generates, including regression models, classification and logistic regression models, and time series prediction models.


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 Released February 19, 2014

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