Tag Archives: Gradient Descent

Logistic Regression 2 – Cost Function, Gradient Descent and Other Optimization Algorithms

We have discussed the basic ideas of logistic regression in previous post.  The purpose of logistic regression is to find the optimal decision boundary which can classify the data with different categorical target feature into different classes.  We also introduced the logistic function or sigmoid function as the regression model to find the optimal decision… Read More »

Linear Regression 4 – Learning Rate and Initial Weights

Choosing Learning Rate We introduced an important parameter, the learning rate α, in Linear Regression 2 – Gradient Descent without discussing how to choose its value.  In fact, the choice of the learning rate affects the performance of the algorithm significantly.  It determines the convergence speed of the gradient descent algorithm, which is the number… Read More »