19 lines
575 B
Python
19 lines
575 B
Python
![]() |
import pandas as pd
|
||
|
import tensorflow as tf
|
||
|
from sklearn.preprocessing import MinMaxScaler
|
||
|
|
||
|
model = tf.keras.models.load_model('model.h5')
|
||
|
|
||
|
data = pd.read_csv('data.csv', sep=';')
|
||
|
|
||
|
data = pd.get_dummies(data, columns=['Sex', 'Medal'])
|
||
|
data = data.drop(columns=['Name', 'Team', 'NOC', 'Games', 'Year', 'Season', 'City', 'Sport', 'Event'])
|
||
|
|
||
|
scaler = MinMaxScaler()
|
||
|
data = pd.DataFrame(scaler.fit_transform(data), columns=data.columns)
|
||
|
|
||
|
X_test = data.filter(regex='Sex|Age')
|
||
|
|
||
|
predictions = model.predict(X_test)
|
||
|
|
||
|
pd.DataFrame(predictions).to_csv('predictions.csv', index=False)
|