Data Science Stack Exchange
Data Science Stack Exchange

Questions tagged [tsne]

t-SNE (t-distributed stochastic neighbor embedding) is a technique for dimensionality reduction.

The t-SNE algorithm is a nonlinear dimensionality reduction method, particularly efficient for transforming high-dimensional data into two or three dimension spaces.

67 questions
20
votes
1 answer

Are t-sne dimensions meaningful?

Are there any meanings for the dimensions of a t-sne embedding? Like with PCA we have this sense of linearly transformed variance maximizations but for t-sne is there intuition besides just the space we define for mapping and minimization of the…
Nitro
  • 407
  • 3
  • 9
15
votes
1 answer

Can closer points be considered more similar in T-SNE visualization?

I understand from Hinton's paper that T-SNE does a good job in keeping local similarities and a decent job in preserving global structure (clusterization). However I'm not clear if points appearing closer in a 2D t-sne visualization can be assumed…
Javierfdr
  • 1,490
  • 12
  • 14
13
votes
1 answer

Does nearest neighbour make any sense with t-SNE?

Answers on here have stated that the dimensions in t-SNE are meaningless, and that the distances between points are not a measure of similarity. However, can we say anything about a point based on it's nearest neighbours in t-SNE space? This answer…
geometrikal
  • 513
  • 1
  • 5
  • 14
12
votes
2 answers

Clustering high dimensional data

TL;DR: Given a big image dataset (around 36 GiB of raw pixels) of unlabeled data, how can I cluster the images (based on the pixel values) without knowing the number of clusters K to begin with? I am currently working on an unsupervised learning…
sunside
  • 223
  • 1
  • 2
  • 8
10
votes
4 answers

What does the long curve-shape t-SNE mean?

I use 1-D CNN input 1*512 size time series data which randomly fragment segment, the output will classify input into 10 classes. After training the CNN, I apply t-SNE to the prediction which I fed in testing data. In general, the output shape of…
Chiao Wei Yeh
  • 101
  • 1
  • 4
10
votes
1 answer

t-SNE: Why equal data values are visually not close?

I have 200 data points that have the same values on all features. After t-SNE dimension reduction they doesn't look so equal anymore, just like this: Why aren't they on the same point in the visualization and even seems to be distributed in two…
ScientiaEtVeritas
  • 201
  • 1
  • 7
9
votes
2 answers

Ways to reconstruct shuffled pixels of a video file?

Suppose that you have a video file which pixel order has been shuffled once. That is, a random order have been defined once and applied to all frames. Does it exist some known approach for retrieving the initial order of pixels? I have some ideas…
Denis Dollfus
  • 93
  • 3
9
votes
4 answers

Is t-SNE just for visualization?

I have used the t-SNE algorithm to visualize my high dimensional data. However, I was wondering if this is a practical method for inference?
smw
  • 203
  • 1
  • 5
7
votes
1 answer

Why it is recommended to use T SNE to reduce to 2-3 dims and not higher dim?

According to wiki it is recommenced to use T-SNE to map to 2-3 dimensional. I can understand this , if we want to visualizing the data. If we want to reduce the number of features (i.e from 30 features to 5 dims), is it recommended to do this with…
Boom
  • 297
  • 1
  • 8
6
votes
3 answers

What Clustering Method Should I Use?

My data is a group of 10 thousand points (each having an node location (x,y)) that are spread across a plane. They are also chromatically-colored based on their weight. I need to finalize a bayesian nonparametric clustering method that groups points…
ChessGrandMaster
  • 61
  • 3
6
votes
2 answers

How to create interactive plot of thousands of images as output of t-SNE?

I have many images that I want to plot as a result of running t-SNE and I want to be able to interactively explore them. matplotlib does not allow enough interactivity to explore, and plotly is too slow. Is there an easy way to plot thousands of…
matwilso
  • 231
  • 2
  • 8
6
votes
2 answers

How to calculate KL-divergence between matrices

Given there are two matrices of dimensionality 100x2 with absolute values ranging from -50 to +50. Is it possible to determine the kl-divergence by applying the entropy algorithm from scipy.stats to the two flattened vectors of size 200?
piutu
  • 61
  • 1
  • 2
5
votes
1 answer

Theoretical differences between KPCA and t-SNE?

I (think I) understand the underlying principles of most dimensionality reduction methods (MDS, IsoMap, t-SNE, Spectral Embedding, Diffusion maps, etc...). Some of the algorithms I use the most are Kernel PCA (with a gaussian kernel) and t-SNE. My…
Rayamon
  • 153
  • 3
5
votes
3 answers

tsne for prediction

I have a traditional prediction setting, with a training data set train and a test data set test. I do not know the outcome y of the test set. I found that tsne separates my binary classification setting quite well. However, tsne cannot really be…
spore234
  • 583
  • 7
  • 14
4
votes
2 answers

If in t-SNE digaram of binary classification both classes follow the similar curve what does t-SNE diagram show?

If in t-SNE digaram of binary classification both classes follow the similar curve what does t-SNE diagram show for instance: Figure1 or Figure2
user10296606
  • 1,784
  • 5
  • 17
  • 31
1
2 3 4 5