Automated Machine Learning (AutoML) for Kaggle Competition

Class TabularClassifier and TabularRegressor are designed for automated generate best performance shallow/deep architecture for a given tabular dataset. (Currently, theis module only supports lightgbm classifier and regressor.)

    clf = TabularClassifier(verbose=True)
    clf.fit(x_train, y_train, time_limit=12 * 60 * 60, data_info=datainfo)

• x_train: string format text data
• y_train: int format text label
• data_info: a numpy.array describing the feature types (time, numerical or categorical) of each column in x_train.

Notes: Preprocessing of the tabular data:

• Class [TabularPreprocessor] involves several automated feature preprocessing and engineering operation for tabular data . *The input data should be in numpy array format for the class TabularClassifier and TabularRegressor .