Vip: Difference between revisions
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===Purpose=== | ===Purpose=== | ||
Calculate Variable Importance in Projection from regression model. | Calculate Variable Importance in Projection from regression model. | ||
===Synopsis=== | ===Synopsis=== | ||
:vip_scores = vip(mode) | :vip_scores = vip(mode) | ||
===Description=== | ===Description=== | ||
Variable Importance in Projection (VIP) scores estimate the importance of each variable in the projection used in a PLS model and is often used for variable selection. A variable with a VIP Score close to or greater than 1 (one) can be considered important in given model. Variables with VIP scores significantly less than 1 (one) are less important and might be good candidates for exclusion from the model. | Variable Importance in Projection (VIP) scores estimate the importance of each variable in the projection used in a PLS model and is often used for variable selection. A variable with a VIP Score close to or greater than 1 (one) can be considered important in given model. Variables with VIP scores significantly less than 1 (one) are less important and might be good candidates for exclusion from the model. | ||
The input is a PLS model structure (model). The output (vip_scores) is a set of column vectors equal in length to the number of variables included in the model. It contains one column of VIP scores for each column of the original calibration y-block. | The input is a PLS model structure (model). The output (vip_scores) is a set of column vectors equal in length to the number of variables included in the model. It contains one column of VIP scores for each column of the original calibration y-block. | ||
See Chong & Jun, Chemo. Intell. Lab. Sys. 78 (2005) 103-112. | See Chong & Jun, Chemo. Intell. Lab. Sys. 78 (2005) 103-112. | ||
===See Also=== | ===See Also=== | ||
[[plotloads]], [[pls]], [[plsda]] | [[plotloads]], [[pls]], [[plsda]] | ||
Revision as of 14:27, 3 September 2008
Purpose
Calculate Variable Importance in Projection from regression model.
Synopsis
- vip_scores = vip(mode)
Description
Variable Importance in Projection (VIP) scores estimate the importance of each variable in the projection used in a PLS model and is often used for variable selection. A variable with a VIP Score close to or greater than 1 (one) can be considered important in given model. Variables with VIP scores significantly less than 1 (one) are less important and might be good candidates for exclusion from the model.
The input is a PLS model structure (model). The output (vip_scores) is a set of column vectors equal in length to the number of variables included in the model. It contains one column of VIP scores for each column of the original calibration y-block.
See Chong & Jun, Chemo. Intell. Lab. Sys. 78 (2005) 103-112.