Sıfırdan Sınıflandırma Modeli: Scikit-learn ile İlk Projeniz

1import numpy as np
2from sklearn.datasets import load_iris
3from sklearn.model_selection import train_test_split
4from sklearn.ensemble import RandomForestClassifier
5from sklearn.metrics import accuracy_score, classification_report
6
7# Veriyi yükle
8iris = load_iris()
9X = iris.data
10y = iris.target
11
12# Veriyi eğitim ve test setine böl
13X_train, X_test, y_train, y_test = train_test_split(
14X, y, test_size=0.2, random_state=42
15)
16
17# Modeli oluştur ve eğit
18model = RandomForestClassifier(n_estimators=100, random_state=42)
19model.fit(X_train, y_train)
20
21# Tahmin yap
22y_pred = model.predict(X_test)
23
24# Başarı oranını ölç
25accuracy = accuracy_score(y_test, y_pred)
26print(f"Doğruluk: {accuracy:.2%}")
27print("\nDetaylı Rapor:")
28print(classification_report(y_test, y_pred, target_names=iris.target_names))

1Doğruluk: 100.00%
2
3Detaylı Rapor:
4precision recall f1-score support
5
6setosa 1.00 1.00 1.00 10
7versicolor 1.00 1.00 1.00 10
8virginica 1.00 1.00 1.00 10

1# Yeni bir çiçek örneğini tahmin et
2new_sample = np.array([[5.1, 3.5, 1.4, 0.2]])
3prediction = model.predict(new_sample)
4print(f"Tahmin edilen tür: {iris.target_names[prediction[0]]}")