Machine Learning week 3 quiz : Logistic Regression
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Logistic Regression
5 试题
Suppose that you have trained a logistic regression classifier, and it outputs on a new example
Our estimate for
Our estimate for
Our estimate for
Our estimate for
Solution: hθ(x) = P(y=1|x;θ) = 1 - P(y=0|x;θ), so the answer is BC
Suppose you have the following training set, and fit a logistic regression classifier
Which of the following are true? Check all that apply.
Adding polynomial features (e.g., instead using
At the optimal value of
Adding polynomial features (e.g., instead using
If we train gradient descent for enough iterations, for some examples
Answer: AB
For logistic regression, the gradient is given by
Answer:AC
Which of the following statements are true? Check all that apply.
Linear regression always works well for classification if you classify by using a threshold on the prediction made by linear regression.
For logistic regression, sometimes gradient descent will converge to a local minimum (and fail to find the global minimum). This is the reason we prefer more advanced optimization algorithms such as fminunc (conjugate gradient/BFGS/L-BFGS/etc).
The cost function
The sigmoid function
Answer:CD
Suppose you train a logistic classifier
Figure:
Figure:
Figure:
Figure:
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