Requests

TrainIIDReqBody

Fields:

• training_data: the raw bytes representing the training data. Is a CSV file as a sting. Should not be accessed directly.
• feature_types: the columns in the training data.
• target: the target Column.
• folds: the number of folds during cross validation.
• validation_data: the optional raw bytes representing the validation data. Should not be accessed directly.
• holdout_data: the optional raw bytes representing the holdout data. Should not be accessed directly.
• fold_assignment_column: an optional field denoting a column representing the fold that each row belongs to. If empty, exodusutils will cut the cv folds by taking the modulo by folds to the row indices.

Methods:

• get_feature_names: returns the names of the columns.
• get_training_df: returns the parsed pandas DataFrame generated from the bytes in training_data. Note that the data types of the columns will correspond to the ones specified in feature_types.
• get_validation_data: returns the parsed pandas DataFrame generated from the bytes in validation_data, or None if there's no validation data.
• get_holdout_data: returns the parsed pandas DataFrame generated from the bytes in holdout_data, or None if there's no holdout data.

PredictReqBody

Fields:

• model_id: the ID of the model you want to predict with.
• data: the raw bytes representing the prediction data. Is a JSON string. Should not be accessed directly.
• threshold: the threshold for classification predictions.
• keep_columns: the columns to keep in the prediction results.

Methods:

• get_prediction_df: takes in a list of Columns, and returns a pandas DataFrame representing the prediction data. The list of Column should be stored into MongoDB once training is completed.