📗 [3 points] Move the sliders below to change the green plane normal so that the largest number of the blue points are above the plane and the largest number of the red points are below the plane. The current number of mistakes is ???.

📗 Answers:
\(w_{1}\) = 0
\(w_{2}\) = 0
\(w_{3}\) = 1
\(b\) = 0

📗 [3 points] Move the sliders below to change the green plane normal so that the total loss from blue points below the plane and the red points above the plane is minimized. The current total cost is ???.

📗 Answers:
\(w_{1}\) = 0
\(w_{2}\) = 0
\(w_{3}\) = 1
\(b\) = 0

📗 [3 points] Which ones of the following functions are equal to the squared error for deterministic binary classification? \(C = \displaystyle\sum_{i=1}^{n} \left(f\left(x_{i}\right) - y_{i}\right)^{2}, f\left(x_{i}\right) \in \left\{0, 1\right\}, y_{i} \in \left\{0, 1\right\}\). Note: \(I_{S}\) is the indicator notation on \(S\).
📗 Note: the question is asking for the functions that are identical in values.
📗 Choices:
\(\displaystyle\sum_{i=1}^{n}\)
\(\displaystyle\sum_{i=1}^{n}\)
\(\displaystyle\sum_{i=1}^{n}\)
\(\displaystyle\sum_{i=1}^{n}\)
\(\displaystyle\sum_{i=1}^{n}\)
None of the above

📗 [3 points] Which one of the following is the gradient descent step for w if the activation function is and the cost function is ?
📗 Choices:
\(w = w - \alpha \displaystyle\sum_{i=1}^{n} \left(a_{i} - y_{i}\right)\)
\(w = w - \alpha \displaystyle\sum_{i=1}^{n} \left(a_{i} - y_{i}\right)\)
\(w = w - \alpha \displaystyle\sum_{i=1}^{n} \left(a_{i} - y_{i}\right)\)
\(w = w - \alpha \displaystyle\sum_{i=1}^{n} \left(a_{i} - y_{i}\right)\)
\(w = w - \alpha \displaystyle\sum_{i=1}^{n} \left(a_{i} - y_{i}\right)\)
None of the above