L3 Logistic Regression Flashcards
(2 cards)
1
Q
Logistic Regression, model
A
- No closed form solution
- Logistic probability model
- Well suited for binary classification
Conditional Bernouilli:
p(y(i) = 1| x(i)) = 1 / (1 + exp(−w^T φ(x(i))) )
General: p(y(i) | x(i)) = 1 / (1 + exp(−y(i) w^T φ(x(i))) )
2
Q
Logistic Regression, optimization
A
Max likelihood: arg min(w) Sum_{(x(i),y(i))∈D} log (1 + exp(−y(i) w^T φ(x(i))) )
Use of gradient descent