fe_pca: Feature Engineering PCA vector addition
In tw1118/myutilitypackage: Helper Functions for Feature Engineering
Description
Usage
Arguments
Value
Description
This function will take in data and add pca feature engineering (PC components) to the original table. For categorical variables,
MCA will be applied for feature reduction.
Usage
1
fe_pca(train, test, pca_var, pca_comp, mca_var, mca_comp)
Arguments
a
train data table
a
test data table
ratio
of variance explained (pca)
a
number of components to be used (pca)
ratio
of variace explained (mca)
a
number of components to be used (mca)
Value
a list with finished two data tables
tw1118/myutilitypackage documentation built on May 16, 2019, 9:13 p.m.
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Description Usage Arguments Value
Description
This function will take in data and add pca feature engineering (PC components) to the original table. For categorical variables, MCA will be applied for feature reduction.
Usage
1 | fe_pca(train, test, pca_var, pca_comp, mca_var, mca_comp)
|
Arguments
a |
train data table |
a |
test data table |
ratio |
of variance explained (pca) |
a |
number of components to be used (pca) |
ratio |
of variace explained (mca) |
a |
number of components to be used (mca) |
Value
a list with finished two data tables
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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