Upload test_models.py

test_models.py

@@ -0,0 +1,27 @@
+import joblib
+import pandas as pd
+
+# Load models and pipeline
+model_rf = joblib.load("rf_model.joblib")
+model_gb = joblib.load("gb_model.joblib")
+model_lr = joblib.load("lr_model.joblib")
+pipeline = joblib.load("pipeline.joblib")
+
+# Create sample input
+sample = pd.DataFrame([{
+    'MOTHER_AGE_GRP': '25–34',
+    'MOTHER_MARITALSTATUS_AT_BIRTH': 'Married',
+    'MOTHER_RESID_COUNTY_TYPE': 'Urban',
+    'SMOKING_DURING_PREG_IND': 'No',
+    'SMOKING_BEFORE_PREG_IND': 'No',
+    'NUM_BIRTHS_BY_MOTHER': 1,
+    'VISITS_IN_1ST_TRIMESTER_IND': 'Yes'
+}])
+
+# Preprocess
+X = pipeline.transform(sample)
+
+# Predict
+print("Logistic Regression Probability:", model_lr.predict_proba(X)[0][1])
+print("Random Forest Probability:", model_rf.predict_proba(X)[0][1])
+print("Gradient Boosting Probability:", model_gb.predict_proba(X)[0][1])