Marrying computer science, statistics and domain expertize
I was reading an article written by Google scientists about how to predict ad click based on user query and the text ad. The article, written by a team of Google scientists - surely experts from top universities - focuses on the very large number of metrics in the model (billions of features), the use of some logistic regression (a statistical technique), and optimization techniques (numerical analysis, gradient methods) to solve the logistic regression (find the optimum regression coefficients). As you would expect, they discuss at length how the feature space is sparse, and how to take advantage of sparsity to design an efficient algorithm.
All of this looks great, and it is certainly a textbook example of a correct, good, interesting application of machine learning. Indeed, in my opinion, this is computer science.
I have two criticisms, and pretty much in all "pure science" stuff that I have read, the criticism is identical. It boils down to...
Read full article at http://bit.ly/1dIOAcm
And please, share and re-post everywhere you can if you want statisticians to regain more visibility in the business world!
You may leave the list at any time by sending the command
SIGNOFF allstat
to [log in to unmask], leaving the subject line blank.
|