Merge pull request #10711 from freqtrade/fix/pytorch-scaling

fix: Update BasePyTorchRegressor.py
This commit is contained in:
Matthias
2024-09-26 18:53:14 +02:00
committed by GitHub
2 changed files with 1 additions and 4 deletions

View File

@@ -86,9 +86,6 @@ class BasePyTorchRegressor(BasePyTorchModel):
dk.feature_pipeline = self.define_data_pipeline(threads=dk.thread_count)
dk.label_pipeline = self.define_label_pipeline(threads=dk.thread_count)
dd["train_labels"], _, _ = dk.label_pipeline.fit_transform(dd["train_labels"])
dd["test_labels"], _, _ = dk.label_pipeline.transform(dd["test_labels"])
(dd["train_features"], dd["train_labels"], dd["train_weights"]) = (
dk.feature_pipeline.fit_transform(
dd["train_features"], dd["train_labels"], dd["train_weights"]

View File

@@ -141,7 +141,7 @@ class PyTorchTransformerRegressor(BasePyTorchRegressor):
pred_df = pd.DataFrame(yb.detach().numpy(), columns=dk.label_list)
pred_df, _, _ = dk.label_pipeline.inverse_transform(pred_df)
if self.freqai_info.get("DI_threshold", 0) > 0:
if self.ft_params.get("DI_threshold", 0) > 0:
dk.DI_values = dk.feature_pipeline["di"].di_values
else:
dk.DI_values = np.zeros(outliers.shape[0])