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

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

# 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")