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Questions tagged [pattern-recognition]

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

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How to use and understand entropy for pattern detection?

I have two images from erp_data and noerp_data matricies. In erp_data we can see a pattern (sigmoid), in no_erp we see no pattern. ERP is event-related potential, if you are curious. My goal is to ...
Vladimir Mikheev's user avatar
2 votes
1 answer
42 views

How to identify patterns/associations in a multiple choice question towards another variable?

I have a dataset where with two questions. Question 1 is a multiple-choice question and asks the participants which treatment they took. E.g., treatment A, treatment B, treatment C etc. Question 2 ...
Gustav's user avatar
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2 votes
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Find pattern in vector data

I have two groups of vectors A = [[0 0 0 0 1], [0 0 0 1 0], …] and B = [[0 0 1 0 1], [0 1 0 0 1], …]. I want to find the pattern that differentiates the vectors in A from the vectors in B. How to do ...
user37959's user avatar
2 votes
0 answers
16 views

Looking to extract patterns from sequences of codes

I have the following problem: I have a registration of people who enter a building, I have the name, entry date and end date. I also have the times at which events occur inside the building. I want to ...
slow_learner's user avatar
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10 views

Dependent and independent variable in PLS regression for sensor array data

I have been using PCA for the pattern recognition of my gas sensor array data. But recently decided to use PLS using OriginPro software. My sensor array data consists of responses coming from 8-10 ...
 Ali Akbar's user avatar
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choosing the number of clips generated arround the selected temporal position?

in the article Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition, it says that for choosing the samples for training from videos: We first select temporal positions ...
anya's user avatar
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1 vote
1 answer
154 views

GLM: invalid value encountered in log special.gammaln

I've never used GLM before so I would like to have some hints on how to use it and if I'm missing any steps. My challenge: I want to know if the price of product is influenced, positively or ...
KeyPi's user avatar
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1 vote
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How to use ML or DL for predicting a value given a pattern

So, I have a folder named Cycles in which I have multiple (say 1000) csv files. Each of this csv file has four parameters and how they vary with time from t=0 to t=900. For more clarity, each csv file ...
Vedang Chavan's user avatar
4 votes
1 answer
110 views

Minimizing the expected loss (PRML)

In Bishop's PRML in section 1.5.2, the author introduces a loss function for classification, which is the expected loss, $$ E[L]=\sum_k \sum_j \int_{R_j} L_{kj}p(\textbf{x},C_k)d\text{x} $$ where Lkj ...
Bruce Murdock's user avatar
1 vote
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22 views

Identifying groups/patterns in a random dataset using Matlab [closed]

I have the datasets which may contain multiple patterns. The data needs to be classified based on grouping in the data. The figure below shows an example of the data. The circles around the data are ...
Mushi's user avatar
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In a specifically ordered set of binary data (ones and zeros), how can you organize them in patterns and from there build a probabilistic network? [duplicate]

So I have a set of 1s and 0s. They are listed in a column on excel. They are listed in a specific order. I do not wish to change their order. So they appear as (1, 0, 1, 0, 0, 1 and so on... 0). Here ...
Paul Adeleke's user avatar
2 votes
1 answer
69 views

Prove that Residuals/Errors are not Predictable [duplicate]

Let's say I have a set of data and I modelled it using an ML algorithm. After I fit multiple models I achieve a certain level of accuracy. It doesn't get better beyond that point. I want to prove ...
Lopez's user avatar
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0 answers
145 views

From the book "Bishop- Pattern Recognition and Machine Learning" Page 31 [closed]

From the book "Bishop- Pattern Recognition and Machine Learning" Page 31. Can you help me derive the equation (1.68) from equations (1.69), (1.70) and (1.71). Please explain every step for ...
bukhari24's user avatar
1 vote
1 answer
70 views

ICA and Gaussian: a misleading example

A book reports that ICA cannot be used if the independent components of the analyzed data are Gaussian (at most one can be Gaussian, but no other). However, in the same book, the following example is ...
volperossa's user avatar
2 votes
2 answers
176 views

Detect quoted text in emails

I have small dataset (<10k) of emails (plaintext) that need to be classified. Currently I'm doing research on topic of email preprocessing and I can't find any suitable solution for quoted text ...
Andrey's user avatar
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How to create piecewise linear and quadratic classifier

Can someone suggests a literature that describe a procedure for projecting a piece-wise linear and piece-wise quadratic classifiers? For example, let's say I have these classes: How would I calculate ...
user366425's user avatar
2 votes
2 answers
132 views

Understanding Equation (3.13) from Bishop's Pattern Recognition and Machine Learning

I'm having trouble deriving the mentioned equation from the text. Specifically, I'm having trouble obtaining the $\mathbf{\phi}(x_n)^T$ term. I checked the errata and while the lack of the $\beta$ ...
Tiberiu's user avatar
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1 vote
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Software to identify or reverse engineer patterns from encoded / decoded data

I have a CSV file that contains encoded date data. I have no idea how the data was encoded, but you can look at the data and see an obvious pattern which means it was probably some sort of custom ...
Martin's user avatar
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3 votes
1 answer
93 views

Distance between two clusters after their joining in centroid linkage

For a distance between two clusters A and B of objects given by $d_{AB}=\left \|{m_{A}-m_{B}} \right \|^{2}$ , where $m_{A}$ is the mean of the objects in cluster $A$, show that the formula ...
loosi95's user avatar
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Identification of a pattern based on given features in time-series data

I am working with electricity time-series data collected at 15 minutes intervals. I am looking for a procedure/theory to find the pattern/sequence in the time-series data based on given features. As I ...
Rajesh Ahir's user avatar
2 votes
1 answer
278 views

Flagging bad time series behavior (Pattern Recognition and Outlier Detection)

I want to get some opinions on how to approach the following problem to do with detecting "unhealthy" behavior in time series data (either using a statistical/analytical model or ML/DL, I do ...
User_13's user avatar
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1 vote
1 answer
33 views

Measure how dataset is harmonious or organized

Suppose we have two set of numbers : A = [1,4,9,16,25,49...100] and B = [1,4,7,7,25,49,64...100]. As you seen the first one is consistently growing, elements of it is square of numbers. But although ...
student0434's user avatar
5 votes
0 answers
54 views

What is the difference between these two types of training?

Suppose that I want to detect if a picture contains a particular logo, for instance the following one. Since template matching would be slow and fail those scaled or resized ones, I decided to train ...
Lerner Zhang's user avatar
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1 vote
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Discover a pattern in a set of spectrograms given a real rating

I'm trying to find patterns in a sorted set of spectrograms, each with a rating. The main idea is to train the CNN in such a way that it understands how the pattern "evolves" at each step, ...
dustedduke's user avatar
1 vote
0 answers
54 views

PCA to identify patterns in the data, forced to a particular variable?

Dataset: I have a hyperspectral dataset that consists 250 wavelength bands (x1,...x250) and corresponding reflectance measurements (y) for each band. Plotting X vs Y yields a spectral profile. I have ...
hcrawford's user avatar
2 votes
3 answers
1k views

How does addition of a regularization term ensures that the matrix is nonsingular? ( least squares )

In Bishop's Pattern recognition book, in 3.1.2 Geometry of least squares section (page 143, last paragraph of section), it is stated that: In practice, a direct solution of the normal equations can ...
Mas A's user avatar
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3 votes
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183 views

Intuition behind random strides in CNNs

I recently attended a lecture on CNNs and was given a brief overview on the topic of dropout. I understood the logic behind the regularization and silencing the firing of neurons to prevent ...
Harduin's user avatar
  • 77
1 vote
0 answers
105 views

Bayesian Parameter estimation (Pattern Classification by Duda, et al

I have been trying to solve question 17 of chapter 3 (Maximum Likelihood and bayesian estimation) of the book "Pattern Classification" by Duda, et al. The question goes as follows: Now the ...
Safi Khan's user avatar
1 vote
0 answers
15 views

Siamese Network for face comparison wont learn, accuracy stuck on 0.5, and loss stuck too [duplicate]

I'm trying to train a siamese network which contains a CNN and an embedding layer at the end to yield 2 similar (close) vectors for 2 images of the same person. I'm using the LFW_Cropped dataset, and ...
Jhon Margalit's user avatar
2 votes
1 answer
104 views

Robustly extracting subpatterns from time-series data

As part of an experiment, I need to collect time-series samples which are tightly associated with some input data. I send this data to an external device, and then collect the associated trace using ...
Deskarano's user avatar
1 vote
1 answer
627 views

What does the meaning of the autocorrelation in this picture?

From this figure, how should I understand what is the lag on the top figure? and when in the bottom figure for example the autocorrelation is 0.45 what does tell us about the above figure? Another ...
Raz's user avatar
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3 votes
2 answers
213 views

If machine learning, in general, is about ‘learning’ patterns, is it correct to say its branches differ based on the type of pattern being learnt?

If machine learning, in general, is about ‘learning’ patterns, is it correct to say its branches differ based on the type of pattern being learnt? I.e. in supervised learning the pattern is a target ...
apprentice9's user avatar
2 votes
0 answers
33 views

How to extract simple shapes from a feature map?

I am working on image parsing project. I want to find a way to automatically parse an object into a list or a graph of simpler shapes. Is there any practical information on how to do so? So far I took ...
aldos's user avatar
  • 21
2 votes
1 answer
174 views

Cluster analysis with interchangeable, binary classes

The Data: I have the results of an experiment where participants were given 30 stimuli and asked to sort them into two groups. The participants were asked to sort them into the two groups without any ...
Julian's user avatar
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1 vote
0 answers
77 views

Avoiding overfitting in unsupervised ML

I am using a unsupervised pattern matching approach to create a trade strategy. I use the output of the pattern matched results to decide whether to enter a trade or not. For deciding the best pattern ...
continuous_learner's user avatar
1 vote
0 answers
702 views

Techniques for finding patterns in binary data

I have a question about data analysis and I am wondering if someone can advise? I am interested in what mathematical techniques are available to look for patterns in binary data. Say I have a black ...
Time4Tea's user avatar
  • 111
1 vote
0 answers
67 views

Comparing probabilites of error for differenct 'k' in a k-NN Classifier

Here is a question that I'm stuck with: Consider two classes $w_1$, $w_2$ in the two-dimensional space. The data from class $w_1$ are uniformly distributed inside a circle of radius $r$. The data of ...
Halfling Wizard's user avatar
2 votes
1 answer
238 views

Explain equation 1.80 in Pattern Recognition and Machine Learning, Bishop

$$E[L] = \sum_k \sum_j \int_{R_j} L_{k,j} p(x, C_k)$$ L is a loss function that returns a real value given a pair (i,j), with i as the index of true class, and j as the index of the predicted class of ...
Jesse's user avatar
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1 vote
1 answer
74 views

Viewing a kernel as a probability density: Why are we only integrating with respect to $x$ and not $x^\prime$?

I am currently studying the textbook Learning with kernels: support vector machines, regularization, optimization and beyond by Schölkopf and Smola. Chapter 1.2 A Simple Pattern Recognition Algorithm ...
The Pointer's user avatar
  • 2,096
1 vote
1 answer
126 views

Q-function in Q-Learning

I ran into solved old-exam question as follows: My notes tell me that option b is correct but I think option d is correct. is there any idea why (b) is correct?
user avatar
2 votes
1 answer
609 views

Information gain of the root node

Recently I saw this question and answer as attached in following image Anyone can add details how this solution achieved?
Harris's user avatar
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1 vote
1 answer
337 views

taylor series expansion in laplace approximation of bayesian neural network prediction

In chapter 6 of the book Pattern recognition and machine learning, there is this part about prediction in Bayesian neural network using laplace approximation : why assuming small variance compared ...
yj_billie's user avatar
1 vote
0 answers
47 views

Chernoff bound for bayes classifier

It's mentioned in many pattern recognition textbooks (Duda, Theodoridis,etc) that Chernoff distance is: but I couldn't find the proof and I wasn't able to derive it myself. Some insight on the ...
ayrt's user avatar
  • 11
2 votes
1 answer
39 views

Why might the functional form of a distribution be "inappropriate" for a particular application?

Working through Bishop's Pattern Recognition and Machine Learning(a great read so far!) and on page 67 he says: "One limitation of the parametric approach is that it assumes a specific ...
stochasticmrfox's user avatar
3 votes
1 answer
1k views

Why maximizing the expected value of log likelihood under the posterior distribution of latent variables maximize the observed data log-likelihood?

I am trying to understand the Expectation-Maximization algorithm and I am not able to get the intuition of a particular step. I am able to verify the mathematical derivation but I want to understand ...
Dibya Prakash Das's user avatar
1 vote
0 answers
617 views

Euclidian distance vs cosine similarity

Currently I'm working on facial recognition. If I use encoding/feature vectors of 2 images which method will prove more accuracy, L2 norm or cosine similarity and why? I read "ICA performs ...
offset-null1's user avatar
0 votes
1 answer
61 views

How can you use a neural network to extract the needed information from social media ads?

How to solve the following problem using neural networks / and machine learning / artificial intelligence? Input data - is an ad from a channel or group of a social network. For example, this: A room ...
Vitaly Vesyolko's user avatar
1 vote
0 answers
21 views

Question about package 'dtw' in R [closed]

Please see below images. Using package 'dtw' in R, is there a way to ensure that pattern 1) has a lower computed distance relative to the reference pattern than pattern 2) does. In other words, can ...
Bryan Franco's user avatar
0 votes
0 answers
37 views

How can I determine a gaussian field for thresholding a distribution at each location of a grid?

Suppose $X(u, v) \in R$ is a random variable at location $(u,v)$ of a grid $G \subset R^2$, and $X(u,v)$ can be expectedly decomposed into two components with a unknown threshold $t(u,v)$ with $t(u,v) ...
tunar's user avatar
  • 533
0 votes
0 answers
39 views

What is the best structure (Accuracy of the text extracted) for building an OCR? ATTENTION, CRNNN, DRAM,RAM, CTC based

If I want to make a new OCR for extracting text from textbooks, specially maths and chemistry, what should be the structure for the OCR? THERE ARE LOT OF TUTORIALS around the internet but no one ...
Deshwal's user avatar
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