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• Random-Forest classifier for classifying backorder data
• The data is imbalance between 2 label
• Duplicating the Positive-label or Re-sampling the Negative-label to get more balance data-set
• Data setBackorder data

Dependencies:

• pandas: read / write csv file
• numpy: data format
• sklearn: classifiers

• Training from csv data-file and writing model to model-fileorder_classifier.training_from_csv_data(data_file, model_file)

• Loading model from model-fileorder_classifier.readModel(file_path)

• Read from file and convert data to numpy formatorder_preprocess.read_data(file_path)

• Predictorder_classifier.predict(data, classifier)

• Training sampleorder_classifier.build_classifier_sample()

• Evaluating sampleorder_classifier.eval_result_rf()