def deserialize_gaussian_nb(model_dict): model = GaussianNB(model_dict['params']) model.classes_ = np.array(model_dict['classes_']) model.class_count_ = np.array(model_dict['class_count_']) model.class_prior_ = np.array(model_dict['class_prior_']) model.theta_ = np.array(model_dict['theta_']) model.sigma_ = np.array(model_dict['sigma_']) model.epsilon_ = model_dict['epsilon_'] return model
def NB_predict(): X = json.loads(request.form['X']) params = json.loads(request.form['params']) clf = GaussianNB() clf.class_prior_ = np.array(params['class_prior']) clf.class_count_ = np.array(params['class_count']) clf.theta_ = np.array(params['theta']) clf.sigma_ = np.array(params['sigma']) clf.classes_ = np.array(params['classes']) y = clf.predict(X) return jsonify(pred=y.tolist())