refactor(Project): removed regression method (we can still use regression models, but we'll need map them to classification later) (#182)

* refactor(Project): removed regression method (we can still use regression models, but we'll need map them to classes later)

* fix(Training): removed mistakenly left in `method` parameter

training/meta_labeling.py

@@ -2,7 +2,6 @@ from utils.evaluate import discretize_threeway_threshold, evaluate_predictions
 from utils.helpers import equal_except_nan
 from training.primary_model import train_primary_model
 import pandas as pd
-from models.model_map import default_feature_selector_classification, default_feature_selector_regression
 from models.base import Model
 from reporting.types import Reporting
 from typing import Union, Optional
@@ -35,7 +34,6 @@ def train_meta_labeling_model(
         y = meta_y,
         target_returns = target_returns,
         models = models,
-        method = 'classification',
         expanding_window = training_config['expanding_window_meta_labeling'],
         sliding_window_size = training_config['sliding_window_size_meta_labeling'],
         retrain_every = training_config['retrain_every'],
@@ -59,7 +57,6 @@ def train_meta_labeling_model(
         target_returns = target_returns,
         y_pred = avg_predictions_with_sizing,
         y_true = y,
-        method = 'classification',
         no_of_classes = 'two',
         print_results = True,
         discretize=False

training/primary_model.py

@@ -15,7 +15,6 @@ def train_primary_model(
                     y: pd.Series,
                     target_returns: pd.Series,
                     models: list[tuple[str, Model]],
-                    method: Literal['regression', 'classification'],
                     expanding_window: bool,
                     sliding_window_size: int,
                     retrain_every: int,
@@ -80,7 +79,6 @@ def train_primary_model(
             target_returns = target_returns,
             y_pred = preds,
             y_true = y,
-            method = method,
             no_of_classes=no_of_classes,
             print_results = print_results,
             discretize=True

training/training_steps.py

@@ -28,7 +28,6 @@ def primary_step(
         y = y,
         target_returns = target_returns,
         models = model_config['primary_models'],
-        method = data_config['method'],
         expanding_window = training_config['expanding_window_primary'],
         sliding_window_size = training_config['sliding_window_size_primary'],
         retrain_every =  training_config['retrain_every'],
@@ -94,9 +93,7 @@ def secondary_step(
             X = current_predictions,
             y = y,
             target_returns = target_returns,
-            models = [model_config['ensemble_model']],
-            method = data_config['method'],
-            expanding_window = False,
+            models = [model_config['ensemble_model']],            expanding_window = False,
             sliding_window_size = 1,
             retrain_every = training_config['retrain_every'],
             from_index = from_index,