revert all changes in normalize_data()

This commit is contained in:
robcaulk 2022-09-03 19:48:30 +02:00
parent c21808ff98
commit 5cfb4154eb

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@ -288,12 +288,11 @@ class FreqaiDataKitchen:
:data_dictionary: updated dictionary with standardized values. :data_dictionary: updated dictionary with standardized values.
""" """
df = data_dictionary["train_features"]
# standardize the data by training stats # standardize the data by training stats
train_max = df.max() train_max = data_dictionary["train_features"].max()
train_min = df.min() train_min = data_dictionary["train_features"].min()
df = ( data_dictionary["train_features"] = (
2 * (df - train_min) / (train_max - train_min) - 1 2 * (data_dictionary["train_features"] - train_min) / (train_max - train_min) - 1
) )
data_dictionary["test_features"] = ( data_dictionary["test_features"] = (
2 * (data_dictionary["test_features"] - train_min) / (train_max - train_min) - 1 2 * (data_dictionary["test_features"] - train_min) / (train_max - train_min) - 1
@ -322,8 +321,8 @@ class FreqaiDataKitchen:
- 1 - 1
) )
self.data[f"{item}_max"] = train_labels_max self.data[f"{item}_max"] = train_labels_max
self.data[f"{item}_min"] = train_labels_min self.data[f"{item}_min"] = train_labels_min
return data_dictionary return data_dictionary
def normalize_single_dataframe(self, df: DataFrame) -> DataFrame: def normalize_single_dataframe(self, df: DataFrame) -> DataFrame: