association

Association

Description: General machine learning helper library that exposes a nearest neighbor algorithm that can be configured to use one of two included types of mesurement. The lib includes two methods to either compare objects as a whole to see what two share the closest similarity or compare the keys from all objects to get the inverse. Supports pearson correlation algo AND euclidean distance algo

Example:

This example will be based off of a group of people rateing movies:

My ratings:

var jordan = {
'Lord of the Rings':4.1,
'The dark night':1.7,
'Sin city':5,
'Friday night lights':2.4
};
==========================

Alec ratings:

var alec = {
'Lord of the Rings':4,
'The dark night':1,
'Sin city':4,
'Friday night lights':4,
'silence of the lambs':5,
'dawn of the dead':6
};
==========================

Randy ratings:

var randy = {
'Lord of the Rings':5,
'The dark night':5,
'Sin city':5,
'Friday night lights':2,
'silence of the lambs':3.9,
'dawn of the dead':5,
'night of the living dead':6
};
==========================

User map:

var userMap = {
alec:alec,
randy:randy
}

With this information we can run a compareAll to see who shares my views in movies.

var association = require('./index.js')
var a = new association({
	formula: 'pearson' // this can also be euclidean
});

a.compareAll(2,userMap,jordan)	

This will return the following(if you use pearson algo)

[ { key: 'alec', score: 0.7033391716221717 },
{ key: 'randy', score: 0.3956282840374718 } ]	

This shows that my movie views match up best with alec.

I can also use this information to get recommendations of movies I have not seen yet.

var association = require('./index.js')
var a = new association({
	formula: 'pearson' // this can also be euclidean
});

a.getRecommendations(a.compareAll(2,userMap,jordan),userMap,jordan)

This will return the following:

[ { key: 'night of the living dead', score: 6 },
{ key: 'dawn of the dead', score: 5.64 },
{ key: 'silence of the lambs', score: 4.603999999999999 } ]

This shows that I will like night of the living dead the most of movies I have not viewed yet followed by dawn of the dead and then silence of the lambs.

Overview:

Methods:

compareAll(num,mapOfMap,baseMap);
	params:
	
		num: the number of returns in the array by the algo
		mapOfMap: the map containing all the maps that will be used 
		for the algo, example map of users movie ratings.
		baseMap: the base map that things will find relation to.
		example: my movie ratings
		
	return:			
		ranking of keys in mapOfMap by comparing objects. //correlation
		
getReccommendations(simObj,mapOfMap,baseMap);
	params:
		
		simObj: the correlation returned by compareAll
		mapOfMap: the map containing all the maps that will be used 
		for the algo, example map of users movie ratings.
		baseMap: the base map that things will find relation to.
		example: my movie ratings
	
	return:			
		ranking of items not included in base map by similarity to existing items.