On Ensemble Methods, the How and Why

Nicely done piece on the topic.  The general overiew motivates the use of all kinds of group solutions, even without analytics methods involved.  We often used them if we were at all uncertain of best solution methods.   They also could give better indication  of the breadth of value in a solution.  Worth reading.

How and why of the ensemble models  in TowardsDataScience  
why does crowd intelligence work?
Dr. Saptarsi Goswami

 There is a famous game show in India named “Kaun Banega Crorepati (KBC)” inspired by “Who wants to be a Millionaire”. It was kind of a quiz show with multiple choices of answers. If the participants can choose the right option for all questions, he or she can win 10 Million Indin Rupees. The participants had some options to resort to if he is unsure about any question. One such option was taking an audience poll and go by the majority choice.

The questions could be from Sports, Mythology, Politics, Music, Movies, Culture, Science, etc that is from a variety of subjects. The audience were no experts of any such subject. Interestingly, more often than not the majority opinion will turn out to be the correct answer. This is the central concept behind ensembling.

Seems like a Magic right, let’s look at the mathematical intuition of the same.
The idea is presented using the following simple diagram, in the context of ML. Now each person is equivalent to a classifier and like the audience is diverse, the more uncorrelated the classifiers better it is.  ... "