Questions tagged [hidden-markov-model]

Hidden Markov Models are used for modelling systems that are assumed to be Markov processes with hidden (i.e. unobserved) states.

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Confusion related to hidden Markov model

I am referring to this tutorial: A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. I am a bit confused about the forward algorithm. From the tutorial: If we ...
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How do I do multiscale HMM classification?

I'm using hidden Markov models to classify some accelerometer data. I take the Fourier transform of the raw data at a given window length, and then train an HMM for each class, and every test instance ...
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In a hidden Markov model, how do all observations and one state give you all states?

$Y^n$ are the observations of our HMM, where $Y_i=a_i$ is a single observation, where $a_i \epsilon \{0,1\}$. For example, $Y^n = k^n$ where $k^n=\{0,1,1,0\}$ $X^n$ are the actual states of our HMM, ...
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Hidden Markov models and anomaly detection

In Shane's answer to this question he suggests that Hidden Markov Models can be used more successfully than wavelets for anomaly / change detection (it was a bit unclear -the topic he was addressing ...
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Hidden Markov Model segmentation of different proportions of binary data

I need to segment a sequence of 0s and 1s by their proportion at relatively large scales. As an example, let's define 5 different states that represent 5 different ratios of 1s & 0s. ...
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Estimating HMM parameters from a sequence with missing observations

The BW algorithm to estimate HMM parameters works on a consecutive sequence of observations. But what should be done if only a partial sequence is available? From another point of view, the observable ...
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Baum-Welch training example

I'm the author of a new Baum Welch trainer using MapReduce for the Apache Mahout project (https://issues.apache.org/jira/browse/MAHOUT-627) I'm looking for an example with a reasonably small data set ...
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HMM ever better than CRF?

For classifying a sequence of instances, are there any specific circumstances that make Hidden Markov Models (HMMs) more accurate than Conditional Random Fields (CRFs)? I have seen several papers ...
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Binary classifier - dividing dataset into training and evaluation sets

I have a Hidden Markov Model for binary classification and two datasets: positive instances negative instances (way more data than the positive ones) In order to evaluate the performance of the ...
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What is the difference between the forward-backward and Viterbi algorithms?

I want to know what the differences between the forward-backward algorithm and the Viterbi algorithm for inference in hidden Markov models (HMM) are.
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How do I account for silent states in decoding/evaluating hidden Markov models?

My end goal is a C++ implementation of a Profile HMM (a profile hidden markov model is a model which contains information about a multiple sequence alignment of proteins; just providing some ...
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Posterior probability vs. Viterbi algorithm

I was working through HMM R package and used posterior as well as Viterbi algorithm: ...
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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 ...
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369 views

Do hidden Markov models contain Markov chains?

Is it correct to say that the Hidden State Sequence in a Hidden Markov Model is a Markov Chain? Thanks
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Are there any *very* user friendly (preferably video) explanations of Baum-Welch?

I'd like to understand the Baum-Welch algorithm. I liked this video on the Forward Backward algorithm: http://www.youtube.com/watch?v=7zDARfKVm7s&feature=related I'm having trouble coming up ...
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Posterior probability using forward backward algorithm in R

For one of my projects I need to find posterior probability of visiting a state S and emitting a symbol. I have built a HMM in R and later I get one observation sequence. But, I am not able to ...
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Difficulty in understanding Hidden Markov Model for syntax parsing using Viterbi algorithm

I intend to apply Kevin Murphy's Hidden markov model (HMM) toolbox. I have a set of production rules(arbitrary) $A_0 \to AB [p=1]$, $A\to aC [p=1]$, $B\to bbC [p=0.5]$, $B\to b [p=0.5]$ where $A_0$ is ...
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Full posterior vs Bayesian Information Criterion for selecting number of HMM states

So I'm looking into methods in selecting the best number of hidden states for a hidden markov model, given I don't know what how many states "generated" my data. One method I've seen a lot is to learn ...
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Public databases of learned HMM models for NLP

I understand that HMM models model language with Parts of Speech (POS) as hidden states and words as observations. These HMM models are usually learned from large text corpora, and many of these ...
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Statistical model of a website

I know that HMMs can be used to construct statistical models of text. Thus, we can generate text according to this model, and compute the likelihood of a text sample under the model. What tools are ...
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Number of states and symbols in multi class Hidden Markov Model classifier

I'm designing a multi class classifier (for 4 classes) using Discrete HMMs with States N and Symbols M for each of the HMM. However, I found that recognition performance(i.e highest log likelihood) ...
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925 views

Classification of observation symbols in a HMM?

I'm new to concept of HMMs. I have trained 2 HMMs separately. HMM1 is trained with symbols A, B, C. HMM2 is trained with symbols D, E, F. I have a set of observation symbols in the set V={A,B,C,...
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Probability and log probability in hidden Markov models

I have a set of Observation Symbol Sequences which I have to test against a set of Trained HMM classifiers. I seem to understand the advantages of using Log Probability over regular probabilities. In ...
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Problem in understanding hidden Markov model EM training and log-lik computation result

i'm using Kevin Murphy's HMM Toolbox. But i have a problem in understanding the results. My problem is to classify some sequences with Hidden Markov Model. I'm using a (test) dataset build with ...
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Observation symbols for training a set of HMMs

If we are to classify 2 separate classes/actions using HMMs, we design 2 separate HMMs (one for each class). Do they share same set or a different set of observations-symbols for each of the HMM? If ...
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Hidden Markov models with Baum-Welch algorithm using python

I'm looking for some python implementation (in pure python or wrapping existing stuffs) of HMM and Baum-Welch. Some ideas? I've just searched in google and I've found really poor material with ...
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Gesture recognition with HMM

I'm approaching at pattern recognition with HMM (with c++ or python). My data are x and y coordinate (normalized between -1,1) of the hand in a recorded video and I want to recognize. This is what I ...
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Implementing Gaussian mixture model for a HMM library

I'm working on an alignment algorithm using LAMP HMM library. This library supports Gaussian probability distribution but it does not seem to support Gaussian Mixture Model. What I want is, to input ...
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Where can I find C++ code samples for HMM (hidden Markov model) as it relates to gesture recognition? [closed]

Any help would be greatly appreciated.
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Trouble applying hidden Markov models

Edit: I updated the question to hopefully make it more easy to understand. I think it was overly complex. I’m having a problem applying hidden Markov models to a game I’m building to learn about ...
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Hidden markov models: output observations defined by a (non-hidden) markov model?

Let me explain what my goal is: I would like to define a hidden markov model with two hidden states and say, five possible observations. As I understand (I'm quite new to HMMs), in each state HMM will ...
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687 views

Application of Hidden Markov Model to CRM

What are some of the applications of a HMM in the marketing field - specifically CRM and targeted marketing? For example, is it mainly for predicting an outcome given a sequence? Such as if web site ...
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243 views

Continuous-states hidden Markov chain

How to deal with HMC that has continuous states? Any papers, links, materials that explain the solution?
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Best way to find non-randomness regions in these or similar count data?

Let say I have data in a shape: [0,0,0,0,1,0,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,2,0,0,0,....] - so mainly zeros.... However I know how long is my 'signal' and how many counts are they. Is it possible ...
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Hidden Markov model (forward algorithm) in R

I have studied some of these resources and I know that there is an R package called HMM. Could anybody explain the usefulness of the 'forward algorithm' with a simple example in R? Finally, I find a ...
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Hidden Markov models and expectation maximization algorithm

Can somebody clarify how hidden Markov models are related to expectation maximization? I have gone through many links but couldn't come up with a clear view. Thanks!
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Problem with k-means used to initialize HMM

I have a sequence of two possible observations ($A$, $B$) and want to train an HMM with $h$ states, namely $\lambda_h$, to predict the probability of the next observation using the Baum-Welch ...
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Calculating confidence intervals via bootstrap on dependent observations

The bootstrap, in its standard form, can be used to calculate confidence intervals of estimated statistics provided that observations are iid. I. Visser et al. in "Confidence Intervals for Hidden ...
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Predicting next character based on few previous — how to combine predictions?

I asked this question at math.stackexchange.com first, but nobody answered. Perhaps statisticians can help me. The question is like this: I have a signal generator, which each second generates one ...
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Is there a concept of “enough” data for training statistical models?

I work on quite a lot of statistical modelling, such as Hidden Markov Models and Gaussian Mixture Models. I see that training good models in each of these cases requires a large (> 20000 sentences for ...
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Number of parameters in Markov model

I want to use BIC for HMM model selection: BIC = -2*logLike + num_of_params * log(num_of_data) So how do I count the number of parameters in the HMM model. ...
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Significance of initial transition probabilites in a hidden markov model

What are the benefits of giving certain initial values to transition probabilities in a Hidden Markov Model? Eventually system will learn them, so what is the point of giving values other than random ...
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Usage of HMM in quantitative finance. Examples of HMM that works to detect trend / turning points?

I am discovering the marvellous world of such called "Hidden Markov Models", also called "regime switching models". I would like to adapt a HMM in R to detect trends and turning points. I would like ...
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Resources for learning Markov chain and hidden Markov models

I am looking for resources (tutorials, textbooks, webcast, etc) to learn about Markov Chain and HMMs. My background is as a biologist, and I'm currently involved in a bioinformatics-related project. ...
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What are the differences between the Baum-Welch algorithm and Viterbi training?

I am currently using Viterbi training for an image segmentation problem. I wanted to know what the advantages/disadvantages are of using the Baum-Welch algorithm instead of Viterbi training.

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