Delete train_model.py

train_model.py

@@ -1,30 +0,0 @@
-from sklearn.datasets import load_iris
-from sklearn.model_selection import train_test_split
-from sklearn.ensemble import RandomForestClassifier
-from sklearn.metrics import accuracy_score, classification_report
-import joblib
-
-# Load the iris dataset
-iris = load_iris()
-X, y = iris.data, iris.target
-
-# Split the data into training and testing sets
-X_train, X_test, y_train, y_test = train_test_split(
-    X, y, test_size=0.2, random_state=42
-)
-
-# Train a RandomForest classifier
-clf = RandomForestClassifier(n_estimators=100, random_state=42)
-clf.fit(X_train, y_train)
-
-# Evaluate the model
-y_pred = clf.predict(X_test)
-accuracy = accuracy_score(y_test, y_pred)
-report = classification_report(y_test, y_pred, target_names=iris.target_names)
-
-print(f"Model Accuracy: {accuracy}")
-print("Classification Report:")
-print(report)
-
-# Save the trained model to a file
-joblib.dump(clf, "iris_model.pkl")