js/tsne.js
function (X) {
			var N = X.length;
			var D = X[0].length;
			assert(N > 0, " X is empty? You must have some data!");
			assert(D > 0, " X[0] is empty? Where is the data?");
			var dists = xtod(X); // convert X to distances using gaussian kernel
			this.P = d2p(dists, this.perplexity, 1e-4); // attach to object
			this.N = N; // back up the size of the dataset
			this.initSolution(); // refresh this
		}
function (X) {
			var N = X.length;
			var D = X[0].length;
			assert(N > 0, " X is empty? You must have some data!");
			assert(D > 0, " X[0] is empty? Where is the data?");
			var dists = xtod(X); // convert X to distances using gaussian kernel
			this.P = d2p(dists, this.perplexity, 1e-4); // attach to object
			this.N = N; // back up the size of the dataset
			this.initSolution(); // refresh this
		}
function ( X ) { var N = X . length ; var D = X [ 0 ] . length ; assert ( N > 0 , " X is empty? You must have some data!" ) ; assert ( D > 0 , " X[0] is empty? Where is the data?" ) ; var dists = xtod ( X ) ; // convert X to distances using gaussian kernel this . P = d2p ( dists , this . perplexity , 1e-4 ) ; // attach to object this . N = N ; // back up the size of the dataset this . initSolution ( ) ; // refresh this }
this function takes a set of high-dimensional points and creates matrix P from them using gaussian kernel
this function takes a set of high - dimensional points and creates matrix P from them using gaussian kernel