Cutoff Threshold of Variable Importance in Projection for Variable Selection
نویسندگان
چکیده
At present, variable selection turns to prominence since it obviously alleviate a trouble of measuring multiple variables per sample. The partial least squares regression (PLS-R) and the score of Variable Importance in Projection (VIP) are combined together for variable selection. The value of VIP score which is greater than 1 is the typical rule for selecting relevant variables. Due to a constant cutoff threshold is not sometimes suitable for every data structure, a new cutoff threshold for VIP in classification task has been proposed and then compared to the classical one thru the interesting situation simulation. There were 180 situations generated based on four parameters: Percentage of the number of relevant variables, Magnitude of mean difference of relevant variables between two groups, Degree of correlation between relevant variables, and the sample size. The result of this study presents that the new cutoff threshold can improve in identifying relevant variables more than the previous threshold as seeing of good value of the average balanced accuracy in most of situations. AMS Subject Classification: 62H30
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