Man pages for themis
Extra Recipes Steps for Dealing with Unbalanced Data

adasyn	Adaptive Synthetic Algorithm
bsmote	Borderline-SMOTE Algorithm
circle_example	Synthetic Dataset With a Circle
cluster_centroids	ClusterCentroids Algorithm
cnn	Condensed Nearest Neighbors
enn	Edited Nearest Neighbors
instance_hardness	Remove hard to classify points
kmeans_smote	KMeans-SMOTE Algorithm
ncl	Neighborhood Cleaning Rule
nearmiss	Remove Points Near Other Classes
oss	One-Sided Selection
reexports	Objects exported from other packages
required_pkgs.step	S3 methods for tracking which additional packages are needed...
rose	ROSE Algorithm
smogn	SMOGN Algorithm
smote	SMOTE Algorithm
smoten	SMOTEN Algorithm
smotenc	SMOTENC Algorithm
step_adasyn	Apply Adaptive Synthetic Algorithm
step_bsmote	Apply Borderline-SMOTE Algorithm
step_cluster_centroids	Under-Sampling by Cluster Centroids
step_cnn	Condensed Nearest Neighbors
step_downsample	Down-Sample a Data Set Based on a Factor Variable
step_enn	Edited Nearest Neighbors
step_instance_hardness	Remove hard to classify points
step_kmeans_smote	Apply KMeans-SMOTE Algorithm
step_ncl	Neighborhood Cleaning Rule
step_nearmiss	Remove Points Near Other Classes
step_oss	One-Sided Selection
step_rose	Apply ROSE Algorithm
step_smogn	Apply SMOGN Algorithm
step_smote	Apply SMOTE Algorithm
step_smoten	Apply SMOTEN Algorithm
step_smotenc	Apply SMOTENC Algorithm
step_svmsmote	Apply SVM-SMOTE Algorithm
step_tomek	Remove Tomek's Links
step_upsample	Up-Sample a Data Set Based on a Factor Variable
svmsmote	SVM-SMOTE Algorithm
themis-package	themis: Extra Recipes Steps for Dealing with Unbalanced Data
tomek	Remove Tomek's Links
tunable_themis	tunable methods for themis