def training(data):
print('inside controller')
# removing rows with label values
data = data.dropna(subset=[label])
tabclient = Client(tabpy_serverurl)
# dataframe to json
input_data = json.loads(data.to_json(orient='records'))
returnResult = tabclient.query('RapidMiner_Train', go_url, go_username, go_password, input_data, label,cost_matrix,high_value,low_value,selection_criteria, max_min_crietria_selector, platform)
final_out = json_normalize(returnResult['response'])
return final_out
def quick_training(training_data):
# removing rows with label values
training_data = training_data.dropna(subset=[label])
tabclient = Client(tabpy_serverurl)
# dataframe to json+
responseJSON = training_data.to_json(orient='records')
input_data = json.loads(responseJSON)
returnResult = tabclient.query('Rapidminer_Quick_Training', go_url, go_username, go_password, input_data, label,selection_criteria,max_min_crietria_selector,'tabprep')
final_out = json_normalize(returnResult['response'])
return final_out