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@nicoforteza nicoforteza/train.py
Created Jun 25, 2019

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import pickle
import sys
import os
import json
import traceback
import pandas as pd
from pyod.models.iforest import IForest
# directory where all the info is stored
prefix = "dir/"
# ==== some paths needed
input_path = prefix + 'input/data' # data input path
output_path = os.path.join(prefix, 'output') # output path
model_path = os.path.join(prefix, 'model') # path to save the model
param_path = os.path.join(prefix, 'input/config/hyperparameters.json') # configuration
training_path = os.path.join(input_path, 'train/X.csv')
def train():
# initiate the train
try:
# 1-. Take data and configuration
data = pd.read_csv(training_path, index_col=0)
# Read in any configuration stored
with open(param_path, 'r') as tc:
hyper_parameters = json.load(tc)
# 2-. Set up
# instantiate the Isolation Forest model
model = IForest(contamination=hyper_parameters['contamination'],
behaviour='new')
model.fit(data) # fit
# 3-. Save the model
model_name = 'great_model'
with open(os.path.join(model_path, '{}.pkl'.format(model_name)), 'wb') as out:
pickle.dump(model, out, protocol=0)
# consider that the train fails
except Exception as e:
# write the log
trc = traceback.format_exc()
with open(os.path.join(output_path, 'failure'), 'w') as s:
s.write('Exception during train: ' + str(e) + '\n' + trc)
sys.exit(255)
if __name__ == '__main__':
train()
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