fuweijie / autokaggle

Automated Machine Learning (AutoML) for Kaggle Competition

autokaggle

Automated Machine Learning (AutoML) for Kaggle Competition

Automated tabular classifier tutorial.

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 .