def main():
# First initiate preprocessor and read files which takes 1 - 2 minutes
preprocessing = Preprocessing(
config['weather_file_path'], config['fire_data_file_path'],
['Datetime'], [
'dt_iso', 'temp', 'pressure', 'humidity', 'wind_speed', 'wind_deg',
'rain_1h', 'rain_3h', 'snow_1h', 'snow_3h', 'clouds_all'
])
# start preprocessing
preprocessing.start_preprocessing()
# pass joined weather and fire data to Data class
data = Data(preprocessing.joined_data)
# get train test split
# train data contains 2014 to 2018 years
# test data contains 2019 as prediction year
train_x, train_y, test_x, test_y = data.get_train_test()
xgb = Model((train_x, train_y, test_x, test_y))
xgb.fit()
predictions, target = xgb.make_predict()
description = 'xgb model which contains previous_calls as feature. It exludes weather description feature as it was incearing feature space and was not of importance'
Plot = Plotting(predictions, target, description, xgb)
Plot.start_plotting()
