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March 1, 2019 16:13
liorkPM
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Mar 6, 2019
| """ | ||
| prog_start_time = time.time() | ||
| mlops.init() | ||
| model = pickle.load(open(input_model, "rb")) |
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Should we "try" model loading. In case model not is ready no to get an exception.
| mlops.done() | ||
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| # return predict_results | ||
| return class_probability |
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We return the prediction probability per class and not the predictions. Maybe at least have a configuration for this?
Also do we need another post processing stage to go back to the labels?
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Scikit learn generic predictor, initial checking supporting RF-classifier