| import pandas as pd | |
| import joblib | |
| from sklearn.metrics import classification_report | |
| from evaluation.metrics import calculate_metrics | |
| vectorizer = joblib.load("models/tfidf_vectorizer.pkl") | |
| model = joblib.load("models/logistic_model.pkl") | |
| data = pd.read_csv("evaluation/sample_data.csv") | |
| X = vectorizer.transform(data["text"].astype(str)) | |
| y_true = data["label"] | |
| y_pred = model.predict(X) | |
| metrics = calculate_metrics(y_true, y_pred) | |
| print("Metrics:", metrics) | |
| print("\nClassification Report:") | |
| print(classification_report(y_true, y_pred)) | |