random_forest

besca.tl.auto_annot.random_forest(train, y_train, njobs)

fits a random forest of a thousand esitamtors with balance class weight on training dataset. note: need at least ten nodes

Parameters:

• train (pd.DataFrame) – adata_train.X but scaled and as a dataframe

• y_train (pd.DataFrame) – one dimensional dataframe containing class label

Returns:

trained svm classifier

Return type:

sklearn.ensemble.RandomForestClassifier