منابع مشابه
Visualization of SNPs with t-SNE
BACKGROUND Single Nucleotide Polymorphisms (SNPs) are one of the largest sources of new data in biology. In most papers, SNPs between individuals are visualized with Principal Component Analysis (PCA), an older method for this purpose. PRINCIPAL FINDINGS We compare PCA, an aging method for this purpose, with a newer method, t-Distributed Stochastic Neighbor Embedding (t-SNE) for the visualiza...
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A first line of attack in exploratory data analysis is data visualization, i.e., generating a 2-dimensional representation of data that makes clusters of similar points visually identifiable. Standard JohnsonLindenstrauss dimensionality reduction does not produce data visualizations. The t-SNE heuristic of van der Maaten and Hinton, which is based on non-convex optimization, has become the de f...
متن کاملClustering with t-SNE, provably
t-distributed Stochastic Neighborhood Embedding (t-SNE), a clustering and visualization method proposed by van der Maaten & Hinton in 2008, has rapidly become a standard tool in a number of natural sciences. Despite its overwhelming success, there is a distinct lack of mathematical foundations and the inner workings of the algorithm are not well understood. The purpose of this paper is to prove...
متن کاملVisualizing breast cancer data with t-SNE
One in eight women will get breast cancer in her lifetime and in 2008 it has caused 458.503 deaths among the world [15]. Despite that technology has made considerable improvements in the last decades, there is still room for more advances. A technique that possibly can contribute to this field is t-SNE [24]. The aim of this thesis is to investigate whether t-SNE is able to present the breast ca...
متن کاملVisualizing Data using t-SNE
We present a new technique called “t-SNE” that visualizes high-dimensional data by giving each datapoint a location in a two or three-dimensional map. The technique is a variation of Stochastic Neighbor Embedding (Hinton and Roweis, 2002) that is much easier to optimize, and produces significantly better visualizations by reducing the tendency to crowd points together in the center of the map. ...
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ژورنال
عنوان ژورنال: PLoS ONE
سال: 2013
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0056883