def mars(x_train, x_test, y_train, y_test, timestamp):
# set model
model = Earth(max_degree=1, penalty=1.0, endspan=5)
# predict
model = model.fit(x_train, y_train)
y_pred = model.predict(x_test)
# score
# score=model.score(x_test,y_test)
correlation_matrix = np.corrcoef(y_test, y_pred)
correlation_xy = correlation_matrix[0, 1]
score = correlation_xy**2
MSE, MAD, MAPE = outputReport.regression_basic_results(y_test, y_pred)
fileName, result = outputReport.regression_extanded_results(
timestamp, y_test, y_pred, "mars")
try:
model_summary = str(model.summary())
model_summary_final = model_summary.replace("\n", "<br>")
result += "<br>Model Parameters:<br>" + str(model.get_params(
)) + "<br>Model Summary:<br>" + model_summary_final
except:
result += "<br>Model Summary is not available for MARS"
return score, fileName, MSE, MAD, MAPE, result
def mars_forecast(x_train, x_test, y_train, timestamp):
# set model
model = Earth(max_degree=1, penalty=1.0, endspan=5)
# predict
model = model.fit(x_train, y_train)
y_pred = pd.DataFrame(model.predict(x_test), columns=["Forecasted Values"])
filename = outputReport.regression_extanded_results_forecast(
timestamp, y_pred, "mars forecast")
try:
model_summary = str(model.summary())
model_summary_final = model_summary.replace("\n", "<br>")
result = "<br>Model Parameters:<br>" + str(model.get_params(
)) + "<br>Model Summary:<br>" + model_summary_final
except:
result = "Model Summary is not available for MARS"
result += str(
y_pred.to_html(formatters={'Name': lambda x: '<b>' + x + '</b>'}))
return filename, result
