I have data in following form:
a: 1,2,3,2,3 a: 2,4,5,6,7,8,0,9,7,6,5,6,2 a: 7,8,9,3,4 b: 4,5,3,5,6,3,5,1,2 b: 1,6,3,2,4,5 b: 2,4,5,6,7,8,0,9,7,6,5,6,2 c: 7,8,9,3,4 c: 4,5,3,5,6,3,5,1,2 ...
(in reality, each case has about 100-200 numbers, though the length is variable)
Here, a, b and c are groups (their number is fixed - taken as 3 here) and the numbers indicate a vector associated with each case. How can I apply supervised machine learning with such a data so that if I get a new series of numbers, e.g. following:
I should be able to determine which group (a, b or c) does this case belongs to.
Following features of each list of numbers may be important:
length of series mean value of series variance of series maximum of series minimum of series type of distribution of series (normal or non-normal)
How can I apply machine learning methods to such data. Thanks for your insight.