Kaggle competition: Plant Pathology 2020 - FGVC7
<SOS> metric: MCAUC Kaggle data source: plant-pathology-2020-fgvc7<load_from_csv>
import numpy as np
import pandas as pd
import os
df_base_train = pd.read_csv(".. /input/siim-isic-melanoma-classification/train.csv")
 df_base_test = pd.read_csv(".. /input/siim-isic-melanoma-classification/test.csv" )<define_variables>
dsub = [
pd.read_csv('.. /input/plantpathology/fork-of-plant-2020-tpu-915e9c_version1.csv'),
pd.read_csv('.. /input/plantpathology/plant-pathology-pytorch-efficientnet-b4-gpu_version_7.csv'),
pd.read_csv('.. /input/plantpathology/public-first-score-tpu-incepresnetv2-enb7_version8.csv'),
pd.read_csv('.. /input/plantpathology/classification-densenet201-efficientnetb7.csv'),
pd.read_csv('.. /input/plantpathology/tf-zoo-models-on-tpu.csv'),
]
pd.read_csv('.. /input/plantpathology/tf-zoo-models-on-tpu.csv')
 dsub.append(pd.read_csv('.. /input/plantpathology/fork-of-plant-2020-tpu-915e9c_version1.csv'))
dsub.append(pd.read_csv('.. /input/plantpathology/fork-of-plant-2020-tpu-915e9c_version1.csv'))
n = len(dsub )
train_files = tf.io.gfile.glob(os.path.join(GCS_PATH1, "train*.tfrec"))
if INCLUDE_2019:
train_files += tf.io.gfile.glob([os.path.join(GCS_PATH2, "train%.2i*.tfrec" % i)for i in range(1, 30, 2)])
 if INCLUDE_2018:
train_files += tf.io.gfile.glob([os.path.join(GCS_PATH2, "train%.2i*.tfrec" % i)for i in range(0, 30, 2)])
 if INCLUDE_MALIGNANT:
train_files += tf.io.gfile.glob([os.path.join(GCS_PATH3, "train%.2i*.tfrec" % i)for i in range(15, 30, 1)])
 print("%d train files found" % len(train_files))<train_model>
sub = pd.read_csv('.. /input/plant-pathology-2020-fgvc7/sample_submission.csv')
 sub.head()
<prepare_x_and_y><EOS> 
sub.healthy = 0
sub.multiple_diseases = 0
sub.rust = 0
sub.scab = 0
for d in dsub:
sub.healthy += d.healthy
sub.multiple_diseases += d.multiple_diseases
sub.rust += d.rust
sub.scab += d.scab
sub.healthy = sub.healthy/n
sub.multiple_diseases = sub.multiple_diseases/n
sub.rust = sub.rust/n
sub.scab = sub.scab/n
sub.to_csv('submission.csv', index=False)
 sub.head()