stratified cross validation

Stratified cross validation is a data validation technique which is used when splitting the ML dataset into k subsets, of which k-1 subsets are used as training subsets (folds) and one (1) is used as the test subset (fold). This process is repeated k times. Stratified cross validation uses stratified sampling in the dataset, in … Read more


SVM stands for Support Vector Machine. SVM is a well-known family of supervised learning non-parametric algorithms which are used in regression and classification machine learning problems, by separating data values using a hyperplane. SVM algorithms are ideal when there is presence of outliers in the model training data.