Kaggle competition: SIIM-ISIC Melanoma Classification
<SOS> metric: MCAUC Kaggle data source: siim-isic-melanoma-classification<set_options>
import numpy as np
import pandas as pd
import os
%matplotlib inline 
<define_variables>
sub_path = ".. /input/top-my-submission"
all_files = os.listdir(sub_path )
DATA_PATH = '.. /input'
SUBMISSIONS_PATH = './'
ATOMIC_NUMBERS = {
'H': 1,
'C': 6,
'N': 7,
'O': 8,
'F': 9
}<set_options>
concat_sub['target_mean'] = concat_sub.iloc[:, 1:ncol].mean(axis=1)
 concat_sub['target_median'] = concat_sub.iloc[:, 1:ncol].median(axis=1 )
pd.set_option('display.max_colwidth', -1)
 pd.set_option('display.max_rows', 120)
 pd.set_option('display.max_columns', 120 )<load_from_csv>
concat_sub['target'] = concat_sub['target_mean']
concat_sub[['image_name', 'target']].to_csv('submission_mean.csv',
index=False, float_format='%.6f' )
<load_from_csv><EOS> 
concat_sub['target'] = concat_sub['target_median']
concat_sub[['image_name', 'target']].to_csv('submission_median.csv',
index=False, float_format='%.6f' )