feat(Config): feature extractors are enabled one-by-one with a bool, added previous model to model.fit() (#77)

* feat(Config): feature extractors are enabled one-by-one with a bool, added previous model to model.fit()

* fix(Sweep): removed unused `other_features` parameter that fails sweep

* feat(Config): using preset names for defining feature extractors again

* fix(Tests): fixed model stub classes

models/average.py

@@ -10,7 +10,7 @@ class StaticAverageModel(Model):
     data_scaling = 'unscaled'
     only_column = 'model_'
 
-    def fit(self, X, y):
+    def fit(self, X, y, prev_model):
         # This is a static model, it can' learn anything
         pass
 

models/base.py

@@ -11,7 +11,7 @@ class Model(ABC):
     only_column: Optional[str]
 
     @abstractmethod
-    def fit(self, X, y):
+    def fit(self, X, y, prev_model):
         pass
 
     @abstractmethod
@@ -32,7 +32,7 @@ class SKLearnModel(Model):
     def __init__(self, model):
         self.model = model
 
-    def fit(self, X, y):
+    def fit(self, X, y, prev_model):
         self.model.fit(X, y)
 
     def predict(self, X):

models/momentum.py

@@ -14,7 +14,7 @@ class StaticMomentumModel(Model):
         super().__init__()
         self.allow_short = allow_short
 
-    def fit(self, X, y):
+    def fit(self, X, y, prev_model):
         # This is a static model, it can' learn anything
         pass
 

models/naive.py

@@ -10,7 +10,7 @@ class StaticNaiveModel(Model):
     data_scaling = 'unscaled'
     only_column = None
 
-    def fit(self, X, y):
+    def fit(self, X, y, prev_model):
         # This is a static model, it can' learn anything
         pass