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标签gbm - 这是页3 - GeneraCodice
Does the performance of GBM methods profit from feature scaling?
https://www.generacodice.com/cn/articolo/2681263/does-the-performance-of-gbm-methods-profit-from-feature-scaling
gbm
-
feature-scaling
datascience.stackexchange
Representing cyclical features as sin/cos components
https://www.generacodice.com/cn/articolo/1511917/representing-cyclical-features-as-sin-cos-components
correlation
-
gbm
datascience.stackexchange
Why is there a big drop off in performance in my GBM?
https://www.generacodice.com/cn/articolo/1502311/why-is-there-a-big-drop-off-in-performance-in-my-gbm
gbm
datascience.stackexchange
How to determine if my GBM model is overfitting?
https://www.generacodice.com/cn/articolo/1466540/how-to-determine-if-my-gbm-model-is-overfitting
machine-learning
-
r
-
accuracy
-
gbm
-
overfitting
datascience.stackexchange
GBM与XGBOOST?关键差异?
https://www.generacodice.com/cn/articolo/1128585/gbm与xgboost-关键差异
machine-learning
-
algorithms
-
gbm
-
ensemble-modeling
-
xgboost
datascience.stackexchange
XGBoost是否可以单独处理多重共线性?
https://www.generacodice.com/cn/articolo/1118824/xgboost是否可以单独处理多重共线性
correlation
-
feature-selection
-
gbm
-
xgboost
datascience.stackexchange
可以在数据子集上调整梯度增强回归器并获得相同的结果吗?
https://www.generacodice.com/cn/articolo/1116157/可以在数据子集上调整梯度增强回归器并获得相同的结果吗
scikit-learn
-
gbm
datascience.stackexchange
为什么XGBoost比Sklearn渐变bloostingClassifier快得多?
https://www.generacodice.com/cn/articolo/1115264/为什么xgboost比sklearn渐变bloostingclassifier快得多
scikit-learn
-
gbm
-
xgboost
datascience.stackexchange
XGBOOST中如何合适的成对排名模型?
https://www.generacodice.com/cn/articolo/1113831/xgboost中如何合适的成对排名模型
search
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ranking
-
gbm
-
xgboost
datascience.stackexchange
为什么不将尺寸采样用于梯度提升机(GBM)?
https://www.generacodice.com/cn/articolo/1098849/为什么不将尺寸采样用于梯度提升机-gbm
random-forest
-
accuracy
-
gbm
-
ensemble-modeling
datascience.stackexchange
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