在知识蒸馏过程中，研究者为每个token采样256个logit，并按照教师模型的概率分布进行加权。 学生模型通过交叉熵损失函数学习教师模型的分布。

When using the python / sklearn API of xgboost are the probabilities obtained via the predict_proba method "real probabilities" or do I have to use logit:rawand manually calculate the sigmoid funct...

一、OR值定义 logistic回归分析中的OR值代表“比值比”又称 “优势比”。 OR = 1，X与Y之间没有相关性；OR> 1，X可能会促进Y的出现；OR<1，X会阻碍Y的出现。logistic回归分析可以直接输出OR值， …

I need to improve the prediction result of an algorithm that is already programmed based on logistic regression ( for binary classification). I tried to use XGBoost and CatBoost (with default para...

logit原本是一个函数，它是sigmoid函数（也叫标准logistic函数） p (x) = 1 1 + e x 的反函数： l o g i t (p) = log (p 1 p) 。 logit这个名字的来源即为 log istic un it。 但在深度学习中，logits就是最终的全连接层 …

Basically I was looking for a normalization function part of sklearn, which is useful later for logistic regression. Since I have negative values, I chose MinMaxScaler with: feature_range=(0, 1) a...

死亡的概率为P，则未死亡的概率为1-P，令ln (P/1-P)=logit (P)，这一过程称为logit对数变换。 1. 二元Logistic回归模型 当有多个因素时，Logistic回归的一般形式为： 整个模型以最大似然法进行参数估 …

Scikit-learn indeed does not support stepwise regression. That's because what is commonly known as 'stepwise regression' is an algorithm based on p-values of coefficients of linear regression, and scikit …

此外Logit回归时会提供三个R 方值（分别是M cFadden R 方、Cox & Snell R 方和Nagelkerke R 方），此3个R 方均为伪R 方值，其值越大越好，但其无法非常有效的表达模型的拟合程度，意义相对交小， …

I have achieved 68% accuracy using glm with family = 'binomial' while doing logistic regression in R. I don't have any idea on how to specify the number of iterations through my code. Any suggestio...