Extra Recipes Steps for Dealing with Unbalanced Data


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Documentation for package ‘themis’ version 1.0.3

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adasyn Adaptive Synthetic Algorithm
bsmote borderline-SMOTE Algorithm
circle_example Synthetic Dataset With a Circle
nearmiss Remove Points Near Other Classes
smote SMOTE Algorithm
smotenc SMOTENC Algorithm
step_adasyn Apply Adaptive Synthetic Algorithm
step_bsmote Apply borderline-SMOTE Algorithm
step_downsample Down-Sample a Data Set Based on a Factor Variable
step_nearmiss Remove Points Near Other Classes
step_rose Apply ROSE Algorithm
step_smote Apply SMOTE Algorithm
step_smotenc Apply SMOTENC algorithm
step_tomek Remove Tomek’s Links
step_upsample Up-Sample a Data Set Based on a Factor Variable
tidy.step_adasyn Apply Adaptive Synthetic Algorithm
tidy.step_bsmote Apply borderline-SMOTE Algorithm
tidy.step_downsample Down-Sample a Data Set Based on a Factor Variable
tidy.step_nearmiss Remove Points Near Other Classes
tidy.step_rose Apply ROSE Algorithm
tidy.step_smote Apply SMOTE Algorithm
tidy.step_smotenc Apply SMOTENC algorithm
tidy.step_tomek Remove Tomek’s Links
tidy.step_upsample Up-Sample a Data Set Based on a Factor Variable
tomek Remove Tomek's links