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())
