Month: December 2012

In the final chapter the authors introduce Support Vector Machines (SVM). What SVM do are generalize linear decision boundaries for… Read more

Are you a heavy Twitter user? Would you like to build a custom recommendation system in R that will recommend… Read more

k-nearest neighbors (kNN) is the topic of chapter 10. The authors say it’s the most intuitive of the machine learning… Read more

In this chapter we learn a little about Multidimensional Scaling, or MDS for short. Like PCA in Chapter 8, MDS… Read more

This is a tidy chapter on principle component analysis (PCA). There are many fine tutorials on PCA to be found… Read more

The title of this chapter, “Optimization: Breaking Codes”, sounds more exciting than it really is. The code breaking is attempted… Read more

Chapter 6 covers orthogonal polynomial regression, cross-validation, regularization and a touch of logistic regression. The case study is predicting popularity… Read more