Review of “An improved data characterization method and its application in classification algorithm recommendation” paper by GuangtaoWang, Qinbao Song and Xiaoyan Zhu is now available on Computing Reviews here.

Classification is an active research problem, and numerous classification algorithms have been proposed over the past few years. Some algorithms perform better than others, based on the dataset. “No Silver Bullet” or “No Free Lunch Theorem” is an informal theorem that states that no single classification algorithm outperforms other classification algorithms on all data sets. This informal theorem is essentially what keeps many data scientists in business – each data set has its own idiosyncrasies, and different classification algorithms need to be explored to find the one that best meets the needs of the problem at hand. Continue reading full review.