# Posts Tagged ‘ regressionanalysis ’

## Machine Learning Ex5.1 – Regularized Linear Regression

March 18, 2011
By Exercise 5.1 Improves the Linear Regression implementation done in Exercise 3 by adding a regularization parameter that reduces the problem of over-fitting. Over-fitting occurs especially when fitting a high-order polynomial, that we will try to do here. Data Here's the points we will make a model from: # linear regression mydata = read.csv("http://spreadsheets.google.com/pub?hl=en_GB&hl=en_GB&key=0AnypY27pPCJydGhtbUlZekVUQTc0dm5QaXp1YWpSY3c&output=csv", header = TRUE) # view data plot(mydata) ## Machine Learning Ex4 – Logistic Regression and Newton’s Method

March 16, 2011
By Exercise 4 is all about using Newton's Method to implement logistic regression on a classification problem. For all this to make sense i suggest having a look at Andrew Ng machine learning lectures on openclassroom. We start with a dataset representing 40 students who were admitted to college and 40 students who were not admitted, and their corresponding...

## Machine Learning Ex3 – multivariate linear regression

March 8, 2011
By Exercise 3 is about multivariate linear regression. First part is about finding a good learning rate (alpha) and 2nd part is about implementing linear regression using normal equations instead of the gradient descent algorithm. Data As usual hosted in google docs: mydata = read.csv("http://spreadsheets.google.com/pub?key=0AnypY27pPCJydExfUzdtVXZuUWphM19vdVBidnFFSWc&output=csv", header = TRUE) # show last 5 rows tail(mydata, 5) area bedrooms price 43 2567 ...

## Machine Learning Ex2 – linear regression

February 24, 2011
By Andrew Ng has posted introductory machine learning lessons on the OpenClassRoom site. I've watched the first set and will here solve Exercise 2. The exercise is to build a linear regression implementation, I'll use R. The point of linear regression is to come up with a mathematical function(model) that represents the data as best as possible, that is done...