import pandas as pd
import numpy as np
from tensorflow import keras
import matplotlib.pyplot as plt
from keras import backend as K
from sklearn.metrics import mean_squared_error

# model = keras.models.load_model('suicide_model.h5')

train = pd.read_csv('train.csv')
test = pd.read_csv('test.csv')
validate = pd.read_csv('validate.csv')

print(train)
# # podział train set
# X_train = train.loc[:, train.columns != 'suicides_no']
# y_train = train[['suicides_no']]
# X_test = test.loc[:, train.columns != 'suicides_no']
# y_test = test[['suicides_no']]

# predictions = model.predict(X_test)

# error = mean_squared_error(y_test, predictions)

# with open('eval_results.txt', 'a') as f:
#     f.write(str(error) + "\n")