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[python-package] How can I use goss in the latest version 4.5 #6603
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Thanks for using LightGBM. As described at https://lightgbm.readthedocs.io/en/latest/Parameters.html#data_sample_strategy, GOSS can be specified via Here's a minimal, reproducible example: import lightgbm as lgb
from sklearn.datasets import make_regression
X, y = make_regression(n_samples=10_000, n_features=10)
reg = lgb.LGBMRegressor(
n_estimators=10,
data_sample_strategy="goss"
)
reg.fit(X, y) If you do that, you'll see this in the logs:
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got it! Thanks a lot.Now I have a new question: __init__(boosting_type='gbdt', num_leaves=31, max_depth=-1, learning_rate=0.1, n_estimators=100, subsample_for_bin=200000, objective=None, class_weight=None, min_split_gain=0.0, min_child_weight=0.001, min_child_samples=20, subsample=1.0, subsample_freq=0, colsample_bytree=1.0, reg_alpha=0.0, reg_lambda=0.0, random_state=None, n_jobs=None, importance_type='split', **kwargs) But no Why can it be directly changed? |
Any other parameters passed to the constructor of As it says at https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html:
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By the way, I reformatted your follow-up question. If you're unsure how I did that, please see https://docs.github.com/en/get-started/writing-on-github/getting-started-with-writing-and-formatting-on-github/basic-writing-and-formatting-syntax. |
In the latest version the parameter "boosting_type" doesn't include "goss" anymore. How can I activate it in the LGBMRegressor
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