Logistic Regression
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- why named logistic regression? (cause losigtic function)
- what is the model?
- how to solve the minimal/maximal problem?
2-class problem
// also lies in 0~1
in all,
假定我们已经学到了最优的
学习的目标是最大化整个样本集合成立的概率:
then gradient descent could be applied to solve the
Multi-class problem
give the constrain the probability of different class:
The
SMLR - Sparse multinomial Logistic Regression
In total
the weight vector for one of the classes need not be estimated. Without loss of generality, we thus set
for ordinary softmax regression (also named as multinomial logistic regression-MLR), the probability that
Besides on, add sparsity constraints to the
In SMLR,
- logistic regression
- logistic regression
- logistic regression
- Logistic Regression
- Logistic Regression
- logistic regression
- Logistic Regression
- Logistic Regression
- logistic regression
- Logistic regression
- Logistic Regression
- Logistic Regression
- Logistic Regression
- Logistic Regression
- Logistic Regression
- logistic regression
- logistic Regression
- Logistic regression
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