def formatKaggleSubmission(predictions, model_id):
# predictions is dataframe containing test data set predictions created
# by the ModelTrainer()
# returns submission dataframe with correctly formatted submission data set
#
#
# get parameters
#
from msw.model_stacking import getConfigParameters
CONFIG = getConfigParameters()
submission = predictions[CONFIG['ID_VAR']].join(predictions[model_id +
'_1'])
submission.columns = CONFIG['KAGGLE_SUBMISSION_HEADERS']
return submission
#%%
from msw.model_stacking import FeatureGenerator, getConfigParameters
#%%
import os.path
import pandas as pd
import numpy as np
#%%
#
# get parameters
#
CONFIG = getConfigParameters()
print('root dir: ',CONFIG['ROOT_DIR'])
#%%
#
# Define Feature Generator for Level 1
#
class FeatureGeneratorNextLevel(FeatureGenerator):
#
# override getRawData() method to handle retrieval of prior
# model predictions
#
def getRawData(self):
