Math Problem Statement
Logistic regression.pdf
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Evaluate the vectorized gradient of the cost function for the logistic model: g(-2.5+0.5X), function, where feature vector X=[1,2,3], and label Y=[0, 0,0], b0?
Solution
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Math Problem Analysis
Mathematical Concepts
Logistic Regression
Gradient Descent
Sigmoid Function
Cost Function
Formulas
Sigmoid function: σ(z) = 1 / (1 + e^-z)
Cost function: J(θ) = -(1/m) Σ [y log(hθ(x)) + (1 - y) log(1 - hθ(x))]
Gradient of the cost function: ∇J(θ) = (1/m) X^T (σ(Xθ) - Y)
Theorems
Maximum Likelihood Estimation
Gradient Descent
Suitable Grade Level
College Level (Advanced Undergrad / Graduate)
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