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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1answer
49 views
Why does differentiating the normalization term of a Binomial Distribution yield the expected value? [on hold]
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 ...
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5 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 ...
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0answers
12 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 ...
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1answer
24 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 ...
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1answer
28 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
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1answer
53 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 ...
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0answers
5 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
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1answer
57 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 ...
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0answers
12 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 ...
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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
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1answer
16 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 ...
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0answers
61 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 ...
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1answer
18 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
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1answer
83 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 $x$, ...
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0answers
13 views
How to evaluate the predicted output in terms of order
I am dealing with a pattern recognition problem, where I need to predict the order of N samples. The concept of classes does not exist here. More specifically, I am ...
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0answers
21 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 ...
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0answers
25 views
singular within scatter matrix and non singular total scatter matrix
When is the scatter matrix in linear discriminant analysis singular although total scatter matrix is non singular ? on which conditions this happens?
Or can you introduce me a book or paper to read ...
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1answer
16 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
20 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
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1answer
46 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; ...
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1answer
28 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
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1answer
103 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
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2answers
44 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" ?...
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1answer
21 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. ...
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2answers
134 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
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1answer
24 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
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1answer
27 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 ...
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0answers
62 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
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1answer
222 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
71 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
16 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 ...
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1answer
266 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 ...
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1answer
43 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
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1answer
150 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 ...
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0answers
30 views
Fingerprint at scale - what is the state of the art?
I'm working on a problem of fraud detection in account opening. When a new user opens an account, we compare a set of three fingerprints against entries in an existing database.
The existing database ...
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0answers
257 views
Convolutional Autoencoder on videos
I'm trying to extract patterns of movement on videos, on a similar way this paper does extracting from images: https://github.com/KBascol/Unsupervised-Interpretable-Pattern-Discovery-in-Time-Series-...
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0answers
25 views
Prediction Model for time series dataset
I have a dataset, which contains measurement values of a mechanical process. The data is being recorded in 1 sec time interval.
The data set contains, recorded measurement value of the process, Lower ...
0
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1answer
58 views
finding a 'standard pattern' from time series data of daily temperature values
Data : I have a time series of temperature values every 5 minutes for 20 days.
There is a common pattern across each day.
Question : What kind of pattern extraction or machine learning algorithm ...
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0answers
36 views
Learning recurring patterns from a stream of bits
I'm trying to find recurring patterns in a stream of bits in order to construct a Gilbert-Eliot model for packet losses and retransmissions in a wireless network. The Model requires interesting ...
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0answers
47 views
Algorithms for detecting pattern shifts in time series data?
I am building a model for time series data that contains ~3 distinct patterns: stable at a 35 deg C, small oscillations around 35C, and large oscillations not centered around 35 deg C. Here is a photo:...
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1answer
47 views
Is this an unsupervised pattern recognition problem?
Consider a feature set containing values of operating condition of an automation unit such as pressure of the valve, temperature, fuel consumption. I want to discover unknown relationship between ...
0
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1answer
10 views
What is a technique for extracting the data pattern from experimental replicates?
I collect the data of air pollution over the year. The data is 2D where the first axis is discrete scale (mass of pollutants in integer; 50, 51, 52...) and another axis is continuous scale (intensity)....
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1answer
64 views
Machine learning in Time series analysis
I will like to do classifiaction with unsupervised learning where the input is a time series. Each sample consisting of 5000 datapoints.
Most people doing time series analysis are interested in ...
0
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1answer
73 views
Detect anomalies in customers behaviour based on their specific recurrent patterns of shopping
I am working on my thesis but I am stuck on the last task to solve.
STEP 1) I have a dataset composed of three variables:
fidelity_card_ID: fidelity card ...
1
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1answer
39 views
Dynamic Time Warping to find distance in stochastic way
Is there a formulation of DTW that allows to deal with uncertainty or to utilize knowledge of the probabilistic structure of the signal? I would like to have a formulation similar to HMM but stay in ...
0
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1answer
84 views
Comparing multidimensional time series with possibly non-informative dimensions
I have several examples of multidimensional time series that correspond to a particular pattern (or class) and form a dictionary. Now, based on these examples I want to find if a new time series ...
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1answer
1k views
Difference between a Poisson process and a Markov process, in terms of applications [closed]
What is the difference between a Poisson process and a Markov process, in terms of applications?
3
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1answer
276 views
Help with derivation of Mean Field Variational Inference
I am studying Variational Inference using Bishop's book: Pattern Recognition and Machine Learning. At the moment, I am struggling to understand the Lower Bound derivation for the Mean-Field ...
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0answers
26 views
how to test the amount of classifier confusion within versus between overarching classes
I am planning a neuroimaging experiment. We present our subjects with 15 items, 5 each in three categories (let's say fruit, animals and people). Each item is presented on 15 instances, for a total of ...
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0answers
91 views
What is the relationship between Eigenface (PCA) & Fisherface (FLDA) on $S_{x} \bigcup S_{y}$?
I have a question about the relationship between the result of Eigenface and Fisherface on face recognition. (Eigenface and Fisherface is the topic of Computer Vision. Those are related with PCA and ...
