Building Machine Learning Systems with Python - Third Edition
by Luis Pedro Coelho, Willi Richert, Matthieu Brucher
Which classifier to use
So far, we have looked at two classical classifiers, namely the decision tree and the nearest neighbor classifier. Scikit-learn supports many more, but it does not support everything that has ever been proposed in academic literature. Thus, one may be left wondering: which one should I use? Is it even important to learn about all of them?
In many cases, knowledge of your dataset may help you decide which classifier has a structure that best matches your problem. However, there is a very good study by Manuel Fernández-Delgado and his colleagues titled, Do we Need Hundreds of Classifiers to Solve Real World Classification Problems? This is a very readable, very practically-oriented study, where the authors conclude that ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access