24 lines
717 B
Python
24 lines
717 B
Python
import numpy as np
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from xgboost import XGBClassifier
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from sklearn.datasets import make_classification
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from sklearn.metrics import accuracy_score
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print("🚀 Testing XGBoost with CUDA GPU...")
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try:
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X, y = make_classification(n_samples=10000, n_features=20, n_classes=2, random_state=42)
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model = XGBClassifier(
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n_estimators=100,
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max_depth=10,
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tree_method="hist",
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device="cuda",
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random_state=42,
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verbosity=1
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)
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print("Training model...")
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model.fit(X, y)
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y_pred = model.predict(X)
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acc = accuracy_score(y, y_pred)
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print(f"✅ Training successful! Accuracy: {acc*100:.2f}%")
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except Exception as e:
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print(f"❌ Error during training: {e}")
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