adelorenzo/stable
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

rollback to the original add noise

Browse Source
This commit is contained in:
longyu 2023-01-31 19:50:39 +01:00
parent b42d396a01
commit dd0713e80f
1 changed files with 5 additions and 19 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

24
freqtrade/freqai/data_kitchen.py
View File

@ -884,25 +884,11 @@ class FreqaiDataKitchen:
"""
Add noise to train features to reduce the risk of overfitting.
"""
da = self.freqai_config["feature_parameters"]["data_augment"]
X = self.data_dictionary['train_features']
y = self.data_dictionary['train_labels']
da_type = da.get("type", "std")
if da_type == "std":
# generate alpha values of 0-mean and 1-std
alpha = np.random.randn(*X.shape)
scale = da.get("vaue", 0.01)
Xaugmented = X + alpha * scale * X.std(0)[None, :]
X = np.vstack((X, Xaugmented))
y = y.append(y)
self.data_dictionary['train_features'] = X
self.data_dictionary['train_labels'] = y
elif da_type == "constant":
mu = 0 # no shift
sigma = self.freqai_config["feature_parameters"]["data_augment"]["value"]
compute_df = self.data_dictionary['train_features']
noise = np.random.normal(mu, sigma, [compute_df.shape[0], compute_df.shape[1]])
self.data_dictionary['train_features'] += noise
mu = 0 # no shift
sigma = self.freqai_config["feature_parameters"]["noise_standard_deviation"]
compute_df = self.data_dictionary['train_features']
noise = np.random.normal(mu, sigma, [compute_df.shape[0], compute_df.shape[1]])
self.data_dictionary['train_features'] += noise
return
def find_features(self, dataframe: DataFrame) -> None: