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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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 ...
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Labeling number sequences seem in a plot [closed]
I have a table with a date and a number.
When I graph the data, I see patterns in the data.
How would I go about labeling the different sequences? There are 4 to 5 sets of numbers including a ...
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27 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 ...
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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 ...
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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 ...
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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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21 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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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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50 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 ...
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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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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\...
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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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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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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 ...
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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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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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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, ...
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1answer
194 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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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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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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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
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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 ...
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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 ...
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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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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 ...
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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 ...
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2answers
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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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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:
...
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1answer
25 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 ...
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1answer
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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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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 ...
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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 ...
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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 ...
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1answer
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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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335 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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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-...
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1answer
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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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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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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 ...
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1answer
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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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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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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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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 ...
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1answer
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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
66 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 ...
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1answer
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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 ...
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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 ...
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1answer
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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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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?
