mirror of
https://github.com/webclinic017/drift.git
synced 2026-07-27 18:57:55 +00:00
Mark Aron Szulyovszky
31 lines
969 B
Python
31 lines
969 B
Python
from __future__ import annotations
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import numpy as np
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from .base import Model
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from sklearn.base import BaseEstimator, ClassifierMixin
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class StaticMomentumModel(BaseEstimator, ClassifierMixin, Model):
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"""
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Model that uses only one feature: momentum. It's positive if momentum is greater than 0, otherwise it's negative.
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"""
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data_transformation = "original"
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only_column = "mom"
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predict_window_size = "single_timestamp"
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def __init__(self, allow_short: bool) -> None:
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super().__init__()
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self.allow_short = allow_short
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def fit(self, X: np.ndarray, y: np.ndarray) -> None:
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# This is a static model, it can' learn anything
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pass
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def predict(self, X) -> np.ndarray:
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negative_class = -1.0 if self.allow_short == True else 0.0
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prediction = 1.0 if X[-1][0] > 0 else negative_class
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return np.array(prediction)
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def predict_proba(self, X) -> np.ndarray:
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return np.array([])
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