Final touches

Author: giacomov

config.yaml

@@ -22,7 +22,7 @@ modeling:
   stratify_by: "neighbourhood_group"
   # Maximum number of features to consider for the TFIDF applied to the title of the
   # insertion (the column called "name")
-  max_tfidf_features: 30
+  max_tfidf_features: 5
   # NOTE: you can put here any parameter that is accepted by the constructor of
   # RandomForestRegressor. This is a subsample, but more could be added:
   random_forest:

src/train_random_forest/run.py

@@ -48,6 +48,9 @@ def go(args):
         rf_config = json.load(fp)
     run.config.update(rf_config)
 
+    # Fix the random seed for the Random Forest, so we get reproducible results
+    rf_config['random_state'] = args.random_seed
+
     ######################################
     # Use run.use_artifact(...).file() to get the train and validation artifact (args.trainval_artifact)
     # and save the returned path in train_local_pat
@@ -60,7 +63,7 @@ def go(args):
     logger.info(f"Minimum price: {y.min()}, Maximum price: {y.max()}")
 
     X_train, X_val, y_train, y_val = train_test_split(
-        X, y, test_size=args.val_size, stratify=X[args.stratify_by]
+        X, y, test_size=args.val_size, stratify=X[args.stratify_by], random_state=args.random_seed
     )
 
     logger.info("Preparing sklearn pipeline")