Warren Woo wuyunfa
wuyunfa
/ randomSinus.py
Created
January 5, 2023 14:16
— forked from benoitdescamps/randomSinus.py
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| import numpy as np | |
| np.random.seed(1) | |
| def f(x): | |
| """The function to predict.""" | |
| return x *np.sin(x) | |
| #---------------------------------------------------------------------- | |
| # First the noiseless case | |
| X = np.atleast_2d(np.random.uniform(0, 10.0, size=100)).T |
wuyunfa
/ XGBOOSTQUANTILE.py
Created
January 5, 2023 14:14
— forked from benoitdescamps/XGBOOSTQUANTILE.py
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| class XGBQuantile(XGBRegressor): | |
| def __init__(self,quant_alpha=0.95,quant_delta = 1.0,quant_thres=1.0,quant_var =1.0,base_score=0.5, booster='gbtree', colsample_bylevel=1, | |
| colsample_bytree=1, gamma=0, learning_rate=0.1, max_delta_step=0,max_depth=3, min_child_weight=1, missing=None, n_estimators=100, | |
| n_jobs=1, nthread=None, objective='reg:linear', random_state=0,reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,silent=True, subsample=1): | |
| self.quant_alpha = quant_alpha | |
| self.quant_delta = quant_delta | |
| self.quant_thres = quant_thres | |
| self.quant_var = quant_var | |
| super().__init__(base_score=base_score, booster=booster, colsample_bylevel=colsample_bylevel, |