# Coursera machine learning week 3 Quiz answer Logistic Regression | Andrew Ng

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### Coursera machine learning week 3 Quiz answer Logistic Regression | Andrew NG

1. Suppose that you have trained a logistic regression classifier, and it outputs on a new example a prediction = 0.2. This means (check all that apply):

•  Our estimate for P(y = 1|x; θ) is 0.8.

h(x) gives P(y=1|x; θ), not 1 – P(y=1|x; θ)

•  Our estimate for P(y = 0|x; θ) is 0.8.

Since we must have P(y=0|x;θ) = 1 – P(y=1|x; θ), the former is
1 – 0.2 = 0.8.

•  Our estimate for P(y = 1|x; θ) is 0.2.

h(x) is precisely P(y=1|x; θ), so each is 0.2.

•  Our estimate for P(y = 0|x; θ) is 0.2.

h(x) is P(y=1|x; θ), not P(y=0|x; θ)

2. Suppose you have the following training set, and fit a logistic regression classifier .   Which of the following are true? Check all that apply.

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