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2. Suppose you are given the following classification task using Logistic Regression: predict the target Y = {0,1} given two real valued features X₁ and X₂. After some training, you learn the following decision rule: [f_W₁X₁ +W₂X₂ +Wo ≥ 0 Predict Y = 1, otherwise predict Y = 0; where model parameters are tuned to w₁ = 3, W₂ = 5, and wo_ - 15. With these values the model is: 3X₁ +5X₂ - 15 = 0 Plot the decision boundary and label the region where we would predict Y = 1 and Y = 0. Hint: Determine the intercept by setting either X₁ = 0 or X₂ = 0

2. Suppose you are given the following classification task using Logistic Regression: predict the target Y = {0,1} given two real valued features X₁ and X₂. After some training, you learn the following decision rule: [f_W₁X₁ +W₂X₂ +Wo ≥ 0 Predict Y = 1, otherwise predict Y = 0; where model parameters are tuned to w₁ = 3, W₂ = 5, and wo_ - 15. With these values the model is: 3X₁ +5X₂ - 15 = 0 Plot the decision boundary and label the region where we would predict Y = 1 and Y = 0. Hint: Determine the intercept by setting either X₁ = 0 or X₂ = 0

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3. Suppose that we learned the above weights using logistic regression. Using this model, what would be our prediction for P (Y=1|X₁, X₂)? (You may want to use the sigmoid function 1 o(z)= = 1+e-²
Transcribed Image Text:3. Suppose that we learned the above weights using logistic regression. Using this model, what would be our prediction for P (Y=1|X₁, X₂)? (You may want to use the sigmoid function 1 o(z)= = 1+e-²
2. Suppose you are given the following classification task using Logistic Regression: predict the target Y = {0, 1} given two real valued features X₁ and X₂. After some training, you learn the following decision rule: If w₁X₁ + W₂X₂ + wo ≥ 0 Predict Y= 1, otherwise predict Y = 0; where model parameters are tuned to w₁ = 3,w₂ = 5, and wo- - 15. With these values the model is: 3X₁ +5X₂ - 15 = 0 Plot the decision boundary and label the region where we would predict Y = 1 and Y = 0. Hint: Determine the intercept by setting either X₁ = 0 or X₂ = 0 10 9 8 87 6 5432TO 1 T -2 -3 -4 -5 -5-4-3-2-1 0 1 2 3 4 5 6 7 8 9 10 +~
Transcribed Image Text:2. Suppose you are given the following classification task using Logistic Regression: predict the target Y = {0, 1} given two real valued features X₁ and X₂. After some training, you learn the following decision rule: If w₁X₁ + W₂X₂ + wo ≥ 0 Predict Y= 1, otherwise predict Y = 0; where model parameters are tuned to w₁ = 3,w₂ = 5, and wo- - 15. With these values the model is: 3X₁ +5X₂ - 15 = 0 Plot the decision boundary and label the region where we would predict Y = 1 and Y = 0. Hint: Determine the intercept by setting either X₁ = 0 or X₂ = 0 10 9 8 87 6 5432TO 1 T -2 -3 -4 -5 -5-4-3-2-1 0 1 2 3 4 5 6 7 8 9 10 +~
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