Extra Recipes Steps for Dealing with Unbalanced Data


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Documentation for package ‘themis’ version 0.1.4

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adasyn Adaptive Synthetic Sampling Approach algorithm
bsmote borderline-SMOTE algorithm
circle_example Synthetic Dataset with a circle
smote SMOTE algorithm
step_adasyn Adaptive Synthetic Sampling Approach
step_bsmote Apply borderline-SMOTE algorithm
step_downsample Down-Sample a Data Set Based on a Factor Variable
step_nearmiss Under-sampling by removing points near other classes.
step_rose Apply ROSE algorithm
step_smote Apply SMOTE algorithm
step_tomek Under-sampling by removing Tomek’s links.
step_upsample Up-Sample a Data Set Based on a Factor Variable
tidy.step_adasyn Adaptive Synthetic Sampling Approach
tidy.step_bsmote Apply borderline-SMOTE algorithm
tidy.step_downsample Down-Sample a Data Set Based on a Factor Variable
tidy.step_nearmiss Under-sampling by removing points near other classes.
tidy.step_rose Apply ROSE algorithm
tidy.step_smote Apply SMOTE algorithm
tidy.step_tomek Under-sampling by removing Tomek’s links.
tidy.step_upsample Up-Sample a Data Set Based on a Factor Variable