Delete train_model.py

train_model.py

@@ -1,31 +0,0 @@
-import pandas as pd
-from sklearn.ensemble import RandomForestClassifier
-from sklearn.preprocessing import LabelEncoder
-import joblib
-
-# Load your dataset
-df = pd.read_csv("mask_dataset.csv")
-
-# Encode features
-face_shape_encoder = LabelEncoder()
-skin_tone_encoder = LabelEncoder()
-style_encoder = LabelEncoder()
-
-X = pd.DataFrame({
-    'face_shape': face_shape_encoder.fit_transform(df['face_shape']),
-    'skin_tone': skin_tone_encoder.fit_transform(df['skin_tone'])
-})
-
-y = style_encoder.fit_transform(df['recommended_style'])
-
-# Train the model
-model = RandomForestClassifier(n_estimators=100, random_state=42)
-model.fit(X, y)
-
-# Save the model and encoders
-joblib.dump(model, "mask_model.pkl")
-joblib.dump(face_shape_encoder, "face_shape_encoder.pkl")
-joblib.dump(skin_tone_encoder, "skin_tone_encoder.pkl")
-joblib.dump(style_encoder, "style_encoder.pkl")
-
-print("✅ Training complete. Model and encoders saved.")