This is a binary classification problem, y has two values (0 or 1), and X (feature) has three dimensions. • Use a logistic regression model to project X to y (classify X into two categories: 0 or 1). • The initialization is: w1 = 0, w2 = 0, w3 = 0, b = 0, Learning rate is 2. • You must use Gradient Descent for logistic regression in this question. • The regression should stop after one iteration. Calculation process and formulas must be included in your answer! You must answer this question by manual calculation, but not programming.
This is a binary classification problem, y has two values (0 or 1), and X (feature) has three dimensions. • Use a logistic regression model to project X to y (classify X into two categories: 0 or 1). • The initialization is: w1 = 0, w2 = 0, w3 = 0, b = 0, Learning rate is 2. • You must use Gradient Descent for logistic regression in this question. • The regression should stop after one iteration. Calculation process and formulas must be included in your answer! You must answer this question by manual calculation, but not programming.
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This is a binary classification problem, y has two values (0 or 1), and X (feature) has three dimensions.
• Use a logistic regression model to project X to y (classify X into two categories: 0 or 1).
• The initialization is: w1 = 0, w2 = 0, w3 = 0, b = 0, Learning rate is 2.
• You must use Gradient Descent for logistic regression in this question.
• The regression should stop after one iteration.
Calculation process and formulas must be included in your answer!
You must answer this question by manual calculation, but not programming.
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