feat(FeatureExtraction): added fractionally differentiated returns to remove lagged returns (#95)

* feat(FeatureExtraction): added fractionally differentiated returns to remove lagged returns

* fix(Sweep): config

* fix(Sweep): name

* fix(Sweep): grid

* feat(Config): separated sliding_window_size_level1 & sliding_window_size_level2

* feat(Dependencies): added ray, now using it to parallel process feature extraction

* fix(Dependencies): added pip explicitly

* fix(Dependencies): removed ray from root

* fix(Models): average model was probably not taking the right timestamp to average

* feat(Config): separated expanding_window_level1 & expanding_window_level2

* fix(Config): set n_features_to_select to the optimal 30

sweep_level_1.yaml

@@ -8,12 +8,23 @@ metric:
 parameters:
     path : 
       value: 'data/'
-    expanding_window:
+    expanding_window_level1:
       values: [True, False]
       distribution: categorical
-    sliding_window_size: 
+    expanding_window_level2:
+      value: False
+    feature_selection:
+      value: True
+    n_features_to_select:
+      values: [10, 20, 30]
+      distribution: categorical
+    dimensionality_reduction:
+      value: True
+    sliding_window_size_level1: 
       values: [180, 280, 380, 480, 580]
       distribution: categorical
+    sliding_window_size_level2: 
+      value: 1
     retrain_every: 
       values: [10, 20, 30]
       distribution: categorical