Function reference • SuperML

Machine Learning Algorithms
`LMTrainer`	Linear Models Trainer
`KMeansTrainer`	K-Means Trainer
`KNNTrainer`	K Nearest Neighbours Trainer
`NBTrainer`	Naive Bayes Trainer
`RFTrainer`	Random Forest Trainer
`XGBTrainer`	Extreme Gradient Boosting Trainer
Helpers
`bm_25()`	BM25 Matching
`Counter()`	Calculate count of values in a list or vector
`CountVectorizer`	Count Vectorizer
`dot()`	Dot product similarity in vectors
`dotmat()`	Dot product similarity between a vector and matrix
`GridSearchCV`	Grid Search CV
`kFoldMean()`	kFoldMean Calculator
`LabelEncoder`	Label Encoder
`normalise1d()`	normalise1d
`normalise2d()`	normalise2d
`RandomSearchCV`	Random Search CV
`sort_index()`	sort_index
`smoothMean()`	smoothMean Calculator
`TfIdfVectorizer`	TfIDF(Term Frequency Inverse Document Frequency) Vectorizer
Datasets
`cla_train`	cla_train
`reg_train`	reg_train

Reference