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

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* 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
This commit is contained in:
Mark Aron Szulyovszky
2022-01-23 17:15:08 +01:00
committed by GitHub
parent 516c8bcc87
commit 5c4a5b0cf1
12 changed files with 11 additions and 44 deletions
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config/config.py
+3 -6
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@@ -25,7 +25,6 @@ def get_dev_config() -> tuple[dict, dict, dict]:
other_features = ['single_mom'],
exogenous_features = ['z_score'],
index_column= 'int',
method= 'classification',
no_of_classes= 'two',
narrow_format = False,
)
@@ -34,7 +33,7 @@ def get_dev_config() -> tuple[dict, dict, dict]:
classification_models = ["LogisticRegression_two_class"]
model_config = dict(
primary_models = regression_models if data_config['method'] == 'regression' else classification_models,
primary_models = classification_models,
meta_labeling_models = [],
ensemble_model = None
)
@@ -69,7 +68,6 @@ def get_default_ensemble_config() -> tuple[dict, dict, dict]:
other_features = ['level_2', 'lags_up_to_5'],
exogenous_features = ['z_score'],
index_column= 'int',
method= 'classification',
no_of_classes= 'two',
narrow_format = False,
)
@@ -80,7 +78,7 @@ def get_default_ensemble_config() -> tuple[dict, dict, dict]:
ensemble_model = 'Average'
model_config = dict(
primary_models = regression_models if data_config['method'] == 'regression' else classification_models,
primary_models = classification_models,
meta_labeling_models = meta_labeling_models,
ensemble_model = ensemble_model
)
@@ -115,7 +113,6 @@ def get_lightweight_ensemble_config() -> tuple[dict, dict, dict]:
other_features = ['level_2'],
exogenous_features = ['z_score'],
index_column= 'int',
method= 'classification',
no_of_classes= 'two',
narrow_format = False,
)
@@ -126,7 +123,7 @@ def get_lightweight_ensemble_config() -> tuple[dict, dict, dict]:
ensemble_model = 'Average'
model_config = dict(
primary_models = regression_models if data_config['method'] == 'regression' else classification_models,
primary_models = classification_models,
meta_labeling_models = meta_labeling_models,
ensemble_model = ensemble_model
)