predict_2017_07_05_2.py 文件源码

def save_results(v, z):
    pred_path = '../submissions/p' + base_data_name() + '.csv'
    all_data_path = '../data/output/model' + base_data_name() + '.csv.gz'

    z.y = np.clip(z.y.values, 1e-5, 1-1e-5)
    z[['y']].to_csv(pred_path, header=None, index=False)

    v['train'] = 1
    z['train'] = 0

    q = pd.concat([v, z], axis=0)
    q.to_csv(all_data_path, index=False, compression='gzip')

    for c in z.columns:
        if c in {'id', 'train', 'y'}: continue
        z[c] = prestore(z[c])
    print(z.head(20))
    print('saved', pred_path, all_data_path)