3
I got the templates from the last five contests at an exam stand.
Templates of multiple choice (A
,B
,C
,D
,E
).
Let’s imagine that the test only has 5 questions, whose templates are:
q1 q2 q3 q4 q5 Prova 1- (A B B C D) Prova 2- (B D E E A) Prova 3- (E E B C C) Prova 4- (D A B C E) Prova 5- (C C A B D)
I want to know the likelihood, in the next contest,
q3
was E
, and the feedback of the next q1
was A
, of q2
was B
, q4
was E
and q5
was D
:
q1 q2 q3 q4 q5 (A B ? E D)
I couldn’t find anything like this on forums in Brazil and abroad. Which classifier should I use in Python? Can someone help?
You can start your analysis by observing the entropy of data.
– Gabriel
Like everything in machine Learning, the answer is: depends, you can use a number of different classifiers depending on how you decide to address the problem, my first choice would be collaborative filtering (https://en.wikipedia.org/wiki/Collaborative_filtering) Note that the animation is very similar to what you want to do. But note that if the alternatives are random between yes, machine Learning can not do much, as the friend above suggested, start by looking at the entropy of the data to know whether or not there is some kind of pattern.
– Victor Capone