Usuń 'predict.py'
This commit is contained in:
parent
f399011471
commit
88b15508c9
31
predict.py
31
predict.py
@ -1,31 +0,0 @@
|
|||||||
import tensorflow as tf
|
|
||||||
import pandas as pd
|
|
||||||
import numpy as np
|
|
||||||
import sklearn
|
|
||||||
import sklearn.model_selection
|
|
||||||
from tensorflow.keras.models import load_model
|
|
||||||
from sklearn.metrics import accuracy_score, precision_score, f1_score
|
|
||||||
|
|
||||||
feature_cols = ['year', 'mileage', 'vol_engine']
|
|
||||||
|
|
||||||
model = load_model('model.h5')
|
|
||||||
test_data = pd.read_csv('test.csv')
|
|
||||||
|
|
||||||
predictions = model.predict(test_data[feature_cols])
|
|
||||||
predicted_prices = [p[0] for p in predictions]
|
|
||||||
|
|
||||||
|
|
||||||
results = pd.DataFrame({'id': test_data['id'], 'year': test_data['year'], 'mileage': test_data['mileage'], 'vol_engine': test_data['vol_engine'], 'predicted_price': predicted_prices})
|
|
||||||
results.to_csv('predictions.csv', index=False)
|
|
||||||
|
|
||||||
y_true = test_data['price']
|
|
||||||
y_pred = y_pred = [round(p[0]) for p in predictions]
|
|
||||||
|
|
||||||
accuracy = accuracy_score(y_true, y_pred)
|
|
||||||
precision = precision_score(y_true, y_pred, average='micro')
|
|
||||||
f1 = f1_score(y_true, y_pred, average='micro')
|
|
||||||
|
|
||||||
with open('metrics.txt', 'w') as f:
|
|
||||||
f.write(f"Accuracy: {accuracy:.4f}\n")
|
|
||||||
f.write(f"Micro-average Precision: {precision:.4f}\n")
|
|
||||||
f.write(f"Micro-average F1-score: {f1:.4f}\n")
|
|
Loading…
Reference in New Issue
Block a user