mirror of
https://github.com/webclinic017/drift.git
synced 2026-08-06 07:37:49 +00:00
Mark Aron Szulyovszky
f762ceed2a
* feat(FeatureExtraction): added fractionally differentiated returns to remove lagged returns * fix(Sweep): config * fix(Sweep): name * fix(Sweep): grid * feat(Config): separated sliding_window_size_level1 & sliding_window_size_level2 * feat(Dependencies): added ray, now using it to parallel process feature extraction * fix(Dependencies): added pip explicitly * fix(Dependencies): removed ray from root * fix(Models): average model was probably not taking the right timestamp to average * feat(Config): separated expanding_window_level1 & expanding_window_level2 * fix(Config): set n_features_to_select to the optimal 30
10 lines
454 B
Python
10 lines
454 B
Python
from fracdiff.sklearn import FracdiffStat
|
|
import pandas as pd
|
|
import numpy as np
|
|
|
|
def feature_fractional_differentiation(df: pd.DataFrame, period: int, is_log_return: bool) -> pd.Series:
|
|
feature_selector = FracdiffStat(window = period)
|
|
input_series = df["close"].to_numpy().reshape(-1, 1)
|
|
feature_selector.fit(input_series)
|
|
result = feature_selector.transform(input_series)
|
|
return pd.Series(np.log(result.squeeze()), index = df.index) |