Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [pattern-recognition]

Refers to techniques for classifying data into categories based on similarities (which can either be known previously, or learned).

Overview

Pattern recognition refers to techniques for classifying data into categories based on similarities (which can either be known previously, or learned).

References

395 questions
160
votes
9 answers

Bottom to top explanation of the Mahalanobis distance?

I'm studying pattern recognition and statistics and almost every book I open on the subject I bump into the concept of Mahalanobis distance. The books give sort of intuitive explanations, but still not good enough ones for me to actually really…
jjepsuomi
  • 5,207
  • 11
  • 34
  • 47
59
votes
10 answers

Measuring entropy/ information/ patterns of a 2d binary matrix

I want to measure the entropy/ information density/ pattern-likeness of a two-dimensional binary matrix. Let me show some pictures for clarification: This display should have a rather high entropy: A) This should have medium entropy: B) These…
Felix S
  • 4,432
  • 4
  • 26
  • 34
49
votes
3 answers

Clustering a long list of strings (words) into similarity groups

I have the following problem at hand: I have a very long list of words, possibly names, surnames, etc. I need to cluster this word list, such that similar words, for example words with similar edit (Levenshtein) distance appears in the same cluster.…
Ufuk Can Bicici
  • 2,028
  • 1
  • 17
  • 26
39
votes
1 answer

Why is Mantel's test preferred over Moran's I?

Mantel's test is widely used in biological studies to examine the correlation between the spatial distribution of animals (position in space) with, for example, their genetic relatedness, rate of aggression or some other attribute. Plenty of good…
Ladislav Naďo
  • 2,202
  • 4
  • 21
  • 45
32
votes
4 answers

The difference of kernels in SVM?

Can someone please tell me the difference between the kernels in SVM: Linear Polynomial Gaussian (RBF) Sigmoid Because as we know that kernel is used to mapped our input space into high dimensionality feature space. And in that feature…
user3378327
  • 951
  • 2
  • 8
  • 11
28
votes
2 answers

How to understand "nonlinear" as in "nonlinear dimensionality reduction"?

I am trying to understand the differences between the linear dimensionality reduction methods (e.g., PCA) and the nonlinear ones (e.g., Isomap). I cannot quite understand what the (non)linearity implies in this context. I read from Wikipedia…
Sibbs Gambling
  • 2,208
  • 5
  • 20
  • 42
25
votes
5 answers

I am learning from Pattern Recognition and Machine Learning, Chris Bishop any good resources?

Are there any videos or other books/notes that anyone has come across that follow Pattern Recognition and Machine Learning by Chris Bishop? I bought this book to learn Machine Learning and am having some trouble getting through it.
FrankTheFrank
  • 373
  • 1
  • 3
  • 4
21
votes
1 answer

number of feature maps in convolutional neural networks

When learning convolutional neural network, I have questions regarding the following figure. 1) C1 in layer 1 has 6 feature maps, does that mean there are six convolutional kernels? Each convolutional kernel is used to generate a feature map based…
user3269
  • 4,622
  • 8
  • 43
  • 53
15
votes
3 answers

Statistical measure for if an image consists of spatially connected separate regions

Consider these two grayscale images: The first image shows a meandering river pattern. The second image shows random noise. I am looking for a statistical measure that I can use to determine if it is likely that an image shows a river pattern. The…
Andy
  • 479
  • 3
  • 10
15
votes
3 answers

State-of-the-art ensemble learning algorithm in pattern recognition tasks?

The structure of this question is as follows: at first, I provide the concept of ensemble learning, further I provide a list of pattern recognition tasks, then I give examples of ensemble learning algorithms and, finally, introduce my question.…
Erba Aitbayev
  • 369
  • 1
  • 5
  • 18
14
votes
3 answers

Hidden Markov model thresholding

I have developed a proof of concept system for sound recognition using mfcc and hidden markov models. It gives promising results when I test the system on known sounds. Although the system, when an unknown sound is inputted returns the result with…
Radek
  • 271
  • 1
  • 6
12
votes
2 answers

Why is Moran's I not equal to "-1" in perfectly dispersed point pattern

Is wikipedia wrong...or I don't understand it? Wikipedia: The white and black squares ("chess pattern") are perfectly dispersed so Moran's I would be −1. If the white squares were stacked to one half of the board and the black squares to the…
Ladislav Naďo
  • 2,202
  • 4
  • 21
  • 45
10
votes
3 answers

Does ICA require to run PCA first?

I reviewed an application-based paper saying that applying PCA before applying ICA (using fastICA package). My question is, does ICA (fastICA) require PCA to be run first? This paper mentioned that ... it is also argued that pre-applying PCA…
Samo Jerom
  • 1,439
  • 2
  • 19
  • 31
10
votes
1 answer

Pattern of mouse (or keybord) clicks and predicting computer user's activity

Based solely on the temporal pattern of mouse clicks (a list of click times $[t_1,t_2,t_3,\ldots]$), is it possible to predict the computer user's activity? For example out of: working vs spending time on Facebook vs watching photos vs playing a…
Piotr Migdal
  • 5,586
  • 2
  • 26
  • 70
10
votes
1 answer

Looking for pattern of events in a time series

I have a time course experiment that follows 8 treatment groups of 12 fish for 24 hours with observations made at 5 second intervals. Among the measurements made is how far each fish travels (in mm) between observations. The 24 hours are divided…
dnagirl
  • 397
  • 4
  • 8
1
2 3
…
26 27