In this post we will see how regularization works to remove the problem of overfitting .We will also check the cost function we will use when we were using regularization. Cost Function We can reduce the weight that some of the terms in our function carry by increasing their cost, if we have problem of …
Regularization in linear and logistic regression Read More »
Classification Problems Classification problems are one of the types of problems in which the variable that we want to predict is valued.So we will learn an algorithm called logistic regression which is widely used and one of the most popular learning algorithm. Here are some examples of classification problems. To check weather an email is …
Large Margin Classification So we have seen many supervised algorithms till now.It does not matter which supervised algorithm we are using, the thing matter is the how much data we are going to use and our skill in applying these algorithms. Support vector machine is also one of the type of algorithm which is very …
So in the last post we have seen about what are the classification problems, hypothesis function and cost function in classification problems. Now in this post we we will see about simplification of that cost function and how to apply gradient descent to fit the parameters of logistic regression. Simplified Cost Function In the last …
Gradient Descent In Classification Problems and Multi class Classification Read More »
So you know most of the basics of linear regression with multiple variables.So in this post we will check about the choice of features that we have and how we can get different learning algorithm.In this post we will also check about polynomial regression which allows us to use the machinery of linear regression to …
Polynomial regression and Parameters computation Read More »