Questions tagged [pattern-recognition]
Refers to techniques for classifying data into categories based on similarities (which can either be known previously, or learned).
357
questions
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0answers
11 views
Limits in exploratory analysis [closed]
I have a question about exploratory analysis. I don't understanding the meaning of the problem, so I am not so sure.
"Give an example of a simple connection, the pattern of which is not or hardly ...
0
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0answers
9 views
Deep learning technique for finding sub pattern
I have a list of strings each with thier target output value. The output in each case is a sub string of the input
Eg
ABCFHDF-> FHD
HJLKSOK-> JLK
GSJKOPS-> JKO
My question is what area of sequence ...
1
vote
0answers
23 views
Identifying original elements in a permutation of a pattern
In the pattern above, the blue peaks are known and are labeled $p_1, p_2, ... p_N$. The red line is the same pattern of peaks, but altered slightly. Given a blue pattern and red pattern, I want to be ...
1
vote
0answers
26 views
How to use the likelihood-ratio to compute the error probability? [closed]
In Bayesian decision theory, There is an analytical form of error rate, which is
$$P(e)=\int P(e|\bf{x})p(\bf{x})d\bf{x}$$.
For binary classification, we can compute the type I error probability with:
...
0
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1answer
53 views
DTW find the warped sequences
I have these 2 sequences:
s1 = [1, 2, 3, 5, 5, 5, 6]
s2 = [1, 1, 2, 2, 3, 5]
And have calculated the DTW matrix as:
...
0
votes
1answer
12 views
Is there a good measure of “paternless-ness” in a set of data?
This may be a slightly open-ended question, or even a bad one, but are there any measures of looking at a set of data and seeing whether there is any kind of pattern or not?
For some context my ...
0
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0answers
11 views
Predict server issues with seperate alert data and incident data
I have the following data -
Server alerts
Server incidents
Given the alert data, my aim is to predict what kind of ticket will be produced in the near future (say 1 week).
I have gone through a ...
1
vote
1answer
64 views
Why is pattern recognition often defined as an ill-posed problem?
A Well-posed problem should have the following properties:
a solution exists
the solution is unique
the solution's behavior changes continuously with the initial conditions.
A problem which is not ...
1
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0answers
12 views
Algorithm for time-domain pattern matching
I have the following problem: I have a hypothesized pattern of a sensor that will most likely fall into four categories A, B, C, or D. Each sample reading contains the same amount of datapoints. My ...
1
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0answers
15 views
Algorithms or techniques for pattern recognition [closed]
I am looking for algorithms or techniques that could be used for pattern recognition/extraction in data. Preferably I would like to know if there are any algorithm implementations in Python that I ...
1
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0answers
14 views
How should I proceed to classify images of not ok microchips
So I have a new project where I have to classify different types of damages on microchips. I am new to machine learning and python in general so I am a little bit lost. I have over 100.000 images I ...
0
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0answers
30 views
Timeseries Pattern recognition
I have about 8000 timeseries from kepler.
Every timeseries is from another star.
Every timeseries are classified into two classes (there is planet orbitting around star, there is no planet).
X axis ...
1
vote
0answers
18 views
Computing the error function defined over a transformed dataset
I am currently reading chapter 5 from Christopher Bishop's Pattern Recognition and Machine Learning book.
Having an infinte dataset $\{({\bf x}, t)\}$, and an estimated value $y({\bf x})$, I am ...
3
votes
1answer
28 views
Ways to extract patterns yielding high scores
Suppose I have a table, containing several features and a score denoting the performance (higher is better) of the corresponding features. Like this:
...
3
votes
0answers
94 views
Which distance metric to use to cluster categorical sequences (clickstreams or clickpaths)?
For my research, I want to cluster website visitors based on their clickstreams to understand different information behavior patterns (i.e., customer/visitor journeys). The data can be characterized ...
0
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1answer
31 views
Practical Examples: Expectation of a function with respect to a probability
I have encountered the following phrasing while reading Bishop's "Pattern Recognition and Machine Learning":
Although for some applications the posterior distribution over unobserved variables will ...
0
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1answer
41 views
Sampling Methods : Pattern Recognition and Machine Learning Bishop
I am reading chapter 11 . Sampling Methods from the book : Pattern Recognition and Machine Learning by Bishop :
In the introduction , in short,he evaluates expectation of some function $f(z)$ with ...
0
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0answers
48 views
data pattern matching with machine learning
Question: How can I automate pattern correlation in data sets.
Context: In oil and gas, picking geological formation tops is a common process. This is performed by matching patterns in the data ...
2
votes
1answer
67 views
Why does differentiating the normalization term of a Binomial Distribution yield the expected value? [closed]
In Bishop's book Pattern Recognition and Machine Learning, problem 2.4 aims to derive the expected value of the binomial distribution $m \sim Bin(N, \mu) = {N \choose m} \mu^m (1 - \mu)^{N-m}$ by ...
0
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0answers
8 views
Clustering items based on response behavior on three tasks
I have a question and was hoping someone could point me in an appropriate direction. I conducted a large experiment and would now like to find patterns in the response behavior of the subjects. The ...
0
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0answers
31 views
Representative Pattern Extraction from Time Series using LSTM
I am interested in extracting a representative pattern from time series having variable time periods. I have attached an image for reference. I would like to know if a LSTM would be the appropriate ...
-1
votes
1answer
142 views
Detecting patterns in time-series data using R
I have a dataset of 258k observations with date time data for each observation in the format of %Y-%m-%d %H:%M:%S. Each observation is a social media post made by a ...
1
vote
1answer
143 views
Finding patterns in various-length binary sequences
I have a large number of binary sequences of different lengths (time-series of observations of the occurrence (1) and non-occurence (0) of some thing) and I am wondering how I could find patterns that ...
1
vote
1answer
116 views
Mean of the posterior distribution in bayesian linear regression with infinitely broad prior
Currently reading from Christopher Bishop's Pattern Recognition and Machine Learning book about parameter distribution under a bayesian linear regression.
On page 153, the author deduces that the ...
0
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0answers
6 views
A simple method for finding the $n$ most distinctive shapes in $x \times y$ pixels region?
Suppose that we have an area made of $x\times y$ pixels. By turning those $x\times y$ many pixels on and off, we can create $2^{x\times y}$ many possible shapes.
But obviously many of those $2^{x\...
2
votes
2answers
660 views
Dealing with imbalanced data-set and cross-validation
I have a data set of brain tumours, 700 malignant, and 225 benign. And I want to build a classification model using SVM, to classify the tumours types based on the data I have. My first question, is ...
0
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0answers
21 views
Using the appropriate method for measuring the similarity of 1-D discrete time series data
I have a data of a 1-D time series data (more than 4000 points), they have fixed spacing, sample at fixed frequency.
My task is to 'extract' the part in this data that match/look similar to my input ...
0
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0answers
29 views
Neural network does not learn and can not generalize [duplicate]
English is not my mother tongue and I'm still a student, so I'll apologize for mistakes.
I made a neural network in java for a school project to recognize the mnist manuscripts. Therefore, I can not ...
2
votes
1answer
27 views
Which machine learning approach to use for data with very low variability and a small training set?
My goal is to write a program which recognizes the chess position in an image of a digital game. I'm not trying to process actual photos of a game in real life, just images like the own below
This ...
1
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0answers
66 views
Hottest news on 'why does Deep Learning work so well' [closed]
At the beginning of last year I was trying to study some papers which were tackling the question "Why does deep learning work so well", but I had to stop due to overwhelming work problems.
I'd love ...
0
votes
1answer
20 views
Modeling words in a language based on their characters
I have different sets of strings, where I assume that each set follows some rules or patterns. For example, the first character must be a number, or the 3rd and the last characters must be the same, ...
0
votes
1answer
366 views
Minimum Input Dimension for Autoencoder Neural Network
Model: Assume we want to learn patterns using an autoencoder neural network. In the simplest case, such a network is "shallow" with 1 hidden layer, takes a $d$-dimensional numerical input vector $x$, ...
0
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0answers
25 views
How do deep CNNs handle problem of “perceptual aliasing” while visual place classification?
Deep CNNs have achieved state-of-the-art performance in image classification. The underlying concept of place recognition is similar to image classification where the task is to classify or recognize ...
1
vote
1answer
17 views
In handwritten digit recognition problem using logistic regression, what changes needed to add another class “Not a Digit”
In handwritten digit recognition problem using logistic regression, normal implementation would forcibly classify even a picture of dog or cat as a digit. To eliminate this, what changes are needed to ...
0
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1answer
22 views
How to make recognition of the important document's attributes
We have a set of PDFs with the different types of documents from the various companies.
The goal: to predict which of them contain some important attributes (for example, document number, customer ...
1
vote
2answers
117 views
Why map the pixel grayscale [0, 1] to [0.01, 0.99] before feeding to the neural network? (MNIST digit recognition)
In this introduction to neural networks (I enjoy it because it builds a digit-recognition neural network from scratch with just numpy, without any high-level NN library like pytorch or tensorflow; ...
0
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1answer
30 views
Suggestions for statistical model/approach to “Pattern recognition for non-uniform time data”
I have a dataset from which I would like to detect recurring patterns (i.e: daily, weekly, monthly). The dataset only contains a time stamp (datetime), and the spacing is non-uniform.
The ...
2
votes
1answer
107 views
How to forecast a set of different time series?
I am trying to forecast a large set of time series that feature very different characteristics. The figure below shows three exemplary series:
My first idea was to identify periodical repetitions as ...
0
votes
2answers
61 views
Can sentiment “analysis” be called sentiment “recognition”? [closed]
In sentiment analysis application of NLP, we are basically required to predict an emotion given a piece of text.
Can we say that we are doing "sentiment recognition" instead of "sentiment analysis" ?...
1
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1answer
22 views
Is there any method to figure out if a random variable has a sine oscillation pattern?
I have a random variable and wondering if there's a mathematical test to see if it has an oscillation pattern like a sine wave.
Data is a time series collected every day and follows a random walk. ...
-2
votes
2answers
137 views
Probability of successful charging based on independent historical or sample data [closed]
I tried my best to find a solution, but failed to find a decent one.
Imagine I want to charge a customer and I have last three days of random charge try data:
...
1
vote
1answer
31 views
Detect cyclic patterns in stream of characters with random noise
I am looking for an algorithm which can detect cyclic pattern in streams of characters which have random noise embedded in them.
An example of cyclic pattern with a set of characters a - m for a ...
0
votes
1answer
29 views
Structure Recognition within images by Machine Learning with scikit-learn
I want to solve the following problem:
Quantify the share (numbers of pixels) of soil, leaves and fruit (ears) within the given image.
For soil, this can easily be solved by looking at one of the ...
1
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0answers
65 views
What is the final goal of RobustPCA methods?
I have an ongoing research that is about clustering and for assigning each data point to a specific cluster, I'm using the Mahalanobis criterion that is gravely based on the covariance matrix of the ...
1
vote
1answer
293 views
Kullback-Leibler divergence is not symmetric but why mutual information is symmetric?
As we know Kullback-Leibler divergence is not symmetric and mutual information is the KL divergence between P(X,Y) and P(X)*P(Y).So my question is that why mutual information is symmetric which is a ...
0
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2answers
153 views
How can PCA eigenvectors be used to classify images?
I have been asked to classify a set of images (which are in two class) using 10 component eigenvectors.
I've got no problem in generating eigenvectors of images, However I have no idea how ...
0
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1answer
18 views
Can you help me understand why there is a $h^d$ but not h in parzen window
Is that because x is d dimension. And when we do the change of variable, we have to do that?
this is where my question comes from:
How to show that the general parzen window provides a probability ...
0
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1answer
441 views
Gesture recognition using hidden Markov model
I am trying to recognise human activity gestures using hidden Markov model. I have created a dataset such that, when I do a particular gesture 10 observation arrays are generated with time. Each ...
-1
votes
1answer
51 views
Extracting characters with certain pattern in R [closed]
I need to extract the characters following certain pattern. For example, I have such text:
AASKI Technology Inc., Tinton Falls, New Jersey, HC1047-18-D-2001;
Accenture Federal Services...(HC1047-...
0
votes
1answer
275 views
How to normalize price data for Dynamic Time Warping?
I'm using package dtw (R) to compare subsets of a price time-series.
I have 100 observations through which I loop a rolling window and extract subsets of 5 consecutive observations. I thus obtain ...
