# 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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### Hidden state models vs. stateless models for time series regression

This is a quite generic question: assume I want to build a model to predict the next observation based on the previous $N$ observations ($N$ can be a parameter to optimize experimentally). So we ...
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### Scaling the backward variable in HMM Baum-Welch

I am just trying to implement the scaled Baum-Welch algorithm and I have run into a problem where my backward variables, after scaling, are over the value of 1. Is this normal? After all, ...
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### Computing Standard Errors in EM algorithm

I'm applying the EM to a hidden markov chain (the $\mathbf{Z}=\{Z_1,...,Z_n\}$ variable), with observations(the $\mathbf{Y}=\{Y_0,...,Y_n\}$ variable) dependent not only on the hidden markov chain, ...
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### Applying HMM to time series data

I have times series data from accelerometer that was attached to a person that was doing different type of exercises. I have a feature matrix that is basically a table with 3 columns (3-axis ...
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### Why isn't a gaussian mixture prone to overfitting?

Consider a Gaussian mixture of 2 components and a dataset of size $N$. The EM algorithm use the data to estimate: the model parameters: the means $\mu_1, \mu_2$ (say the covariances matrices are ...
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### How is prior knowledge of letter/word patterns incorporated into handwriting (or speech) recognition?

Using handwriting recognition as an example, we can train various models to recognise individual characters but to actually be useful we must incorporate prior knowledge of common character sequences, ...
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### HMM library, different length sequences training

I'm using the Kevin Murphy's HMM library in MATLAB(http://www.cs.ubc.ca/~murphyk/Software/HMM/hmm.html) There is a section called 'How to use the toolbox'. There is this example for GMM ouputs: <...
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### How can you use HMMs and ANNs for on-line handwriting recognition?

I've asked this question on cs.stackexchange before. It has a 20-hours remaining bounty there. On-line handwriting recognition is the task of converting a series of $(x(t),y(t))$ coordinates to ...
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### The state-of-the-art methods for speech recognition?

Recently I noticed that Google and Apple have really high quality speech-recognition services. I was wondering about the state-of-the-art methods and techniques they are/might be using to achieve such ...
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### Filtering with HMM

I want to use HMM for filtering, i.e. to find $p(x_t|y_{1:t})$. I see that the forward algorithm calculates the forward variable as a joint probability; $\alpha_t(i) = p(y_{1:t},x_t=S_i|\lambda)$, ...
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### Using R and hidden Markov models to predict pseudorandom binary sequences better than P > .5?

I would to predict a pseudo-random binary sequence of 0's and 1's. I am thinking of using the HMM package in R. I have a binary sequence like ... 0 1 0 0 1 1 0 1 x(n+1)? with thousands of values. ...
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### How to generalize Particle Filters (w.r.t. multiple states)

I'm using particle filters for inference in a hidden markov model with an infinite state-space. My current state-variable is multidimensional and there are interdependencies between some dimensions. I ...
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### How do sudden spikes affect hidden Markov models

I have some data that has two sudden spikes (almost like extreme masses or Dirac delta functions) within my time series data and I was wondering if that is a problem when building hidden Markov models....
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### Baum-welch algorithm: probabilities after each step

In an effort to understand machine learning, at least to some degree, I've been implementing the various algorithms to solve the three problems in a Hidden Markov Model. I've been using Rabiner's ...
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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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### 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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### 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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### Logistic probabilities of state variable in a hidden Markov model always has variance of zero

Here is a simplified version of a more complicated problem that I have. Imagine a hidden Markov model where the state is $X_t\sim N(\mu,\sigma^2)$. The observed variable is $Y_t\sim Bin(N, p_t)$ ...
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### Optimizing this log-likelihood

I have a HMM which emits an observation Z. The parameters of the HMM are $\boldsymbol\theta$. $$\boldsymbol\theta = {\boldsymbol{A},\boldsymbol{B},\pi}$$ Where $\boldsymbol{A}$ is the transition ...
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### A Hidden Markov model with covariates in the transition probabilities

I would like to construct a Hidden Markov model with data about online customer journeys. A well-known concept related to the customer journey literature is the sales funnel. Consumers walk through ...
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### Hidden Markov Models as Dynamic Bayesian Networks

I'm working on a project where I'm trying to classify violent events into different latent states (e.g., low, medium, and high). Each series is distributed Poisson and I'm controlling for population ...
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### HMM (Baum-Welch) - convergence rate differences between the transition and output matrices

I am trying to learn more about the convergence properties of the Baum-Welch algorithm for estimating the HMM parameters. I ran a test comparing the convergence of both the transition and output ...
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### Predicting next event time

Problem definition: Predict user's next event date, based on previous event occurrences. The aim is to inter-corporate time dependent and time independent features. Data: +10 year transactional data ...
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### Using HMM or depmixS4 package to find log-likelihood values

I am trying to implement a Hidden Markov Model. In my studies we used the package HMM as well as wrote our own functions. Here is a slight modification of the example from the HMM package. ...
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### Baum-Welch algorithm variation for Hidden Markov model with reward

Following my previous question on the subject I would like to get your feedback on the following alternative solution. (The original solution to this question is the usage of the POMDP model proposed ...
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### HMM for sequence classification in R

I have a dataset which includes sequence of DNA nucleotides (A,C,G,T) and each sequence has a gene index that is binary. i.e I'm trying to classify unknown sequence by using a hidden markov model in ...
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### How large a training set do I need for an English POS tagger?

I'm trying to implement a POS tagger for English using the Viterbi algorithm on an HMM model. Right now, my results are poor and I'm not sure whether it's due to a bug or due to lack of training data. ...