The task is to apply machine learning to the so-called `primate-factors' dataset. The background is as follows.
Sometime in the early 1980s, an animal behaviour researcher studying the social behaviour of primates was killed in a car accident while returning from a field trip. In his belongings, police discovered several listings of data but the notebooks, assumed to contain details about the origins of the data, were all burned. The longest of the listings is reproduced at ex1-data.txt. This is in tabulated form and it is generally believed that each line records the values of several variables, followed by a value which is either 1 or 0. This is believed to be a classification value of some sort but the nature of the class has never been determined. The final 100 lines in the listing are missing this classification value.
The exercise involves (1) analysing the properties of the data, (2) implementing and then using K - nearest neiobour machine learning method to derive predicted classification values for the final 100 cases.
This needs to be programmed in java.