File size: 1,018 Bytes
fe8d248 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 |
import os.path
import numpy as np
import pandas as pd
import argparse
from sklearn.metrics import mean_squared_error
from sklearn.metrics import mean_squared_log_error
from sklearn.metrics import mean_absolute_error
parser = argparse.ArgumentParser()
parser.add_argument('--path', type=str, required=True)
parser.add_argument('--name', type=str, required=True)
parser.add_argument('--answer_file', type=str, required=True)
parser.add_argument('--predict_file', type=str, required=True)
parser.add_argument('--value', type=str, default="yield")
args = parser.parse_args()
answers = pd.read_csv( args.answer_file)
predictions = pd.read_csv( args.predict_file)
answers.sort_values(by=['id'])
predictions.sort_values(by=['id'])
if 'Age' in predictions:
performance = mean_absolute_error(answers['Age'], predictions['Age'])
else:
performance = mean_absolute_error(answers['Age'], predictions[args.value])
with open(os.path.join(args.path, args.name, "result.txt"), "w") as f:
f.write(str(performance))
|