ium_430705/lab06-eval.py
michalzareba cdc3c79f36 lab06_02
2021-05-10 19:42:26 +02:00

23 lines
702 B
Python

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.layers import Dropout
from tensorflow.keras.callbacks import EarlyStopping
from sklearn.metrics import mean_squared_error, mean_absolute_error, accuracy_score
from tensorflow.keras.models import load_model
import pandas as pd
test_df = pd.read_csv('test.csv')
test_df.drop(test_df.columns[0], axis=1, inplace=True)
x_test = test_df.drop("rating", axis=1)
y_test = test_df["rating"]
model = Sequential()
model = load_model('model_movies')
y_pred = model.predict(x_test.values)
rmse = mean_squared_error(y_test, y_pred)
print(f"RMSE: {rmse}")