Questions tagged [markov-hidden-model]
Hidden Markov Models are a model for understanding and predicting sequential data in statistics and machine learning, commonly used in natural language processing and bioinformatics.
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Are the filtering problem and decoding problem the same thing?
Is there any distinction the filtering problem and the decoding problem?
Wikipedia's definition for a filtering problem is:
The problem of estimating the states or ideally the posterior distribution ...
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HMM - general concept and strategy
I am new to data science and am trying to deal with an HMM on time series - I ran into some problems and I feel I have to rethink my stategy in general. I would love to get some feedback on my ...
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State estimation on live data
I have a time-series dataset that is poisson-distributed and each day I get a new datapoint. If I input all the data into a HMM (hmmlearn in python) it does a very good job at estimating the hidden (...
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options for doing future state prediction for a state machine based on past state transitions
I want to predict future state sequence w.r.t. time of a state machine using information of past state transitions along the time axis. Take a state machine of 5 states 0,1,2,3,4 as an example, the ...
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ML Modeling Recommendation for Predicting Snake Encounters in Historical Journey Data
I have a dataset consisting of historical journey data where individuals travel from point A to point B. During their journeys, they may encounter varying numbers of animal sightings, including snakes....
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Hidden Markov Model is not accurate with me
I am new to Speech Recognition and want to implement a simple words classifier that predicts the spoken word is one of the 100 words I have in my system. So I have a dataset of audios with every ...
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Can you learn about Hidden Markov Models with Gaussian Mixture Models?
I am using both somewhat concurrently: I notice that the both have and entanglement of the number of features and number of components. Also, both describe covariance matrices in the same way.
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Does 'Hidden' mean that we do not know how the emissions interact with the transitions, in a Hidden Markov Model?
The models online are all easy to read except for one thing that confuses me. I do not see how the two matrices interact.
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Understanding MDP variants and "model-free" RL algorithms
RL is based on MDPs. But MDPs have other useful variants such as Semi MDP (variable time), POMDP (partially observable states) etc.
Some industrial problems seem to be better suited for SMDP and/or ...
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Comparing time series classification with Hidden Markov Model vs Dynamic Time Warping - which model should I use to generate data?
Copied from Cross Validated
I am writing a thesis which compares two approaches to time series classification: Hidden Markov Models and Dynamic Time Warping combined with 1-NN. I'll apply both ...
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How to link/relate predicted entities in named entity recognition?
I have developed a NER model to detect all address and property price independently in a pdf document which have property address and its prices in natural language. There are lots of variations in ...
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Problem understanding the forward algorithm for HMMs
I found a recursive version of the forward algorithm on wikipedia, however I don't understand the notation given in the pseudocode:
What means $$x_{t-1}$$ under the summation sign? What do I need to ...
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Which python library for supervised learning of HMMs?
I have a dataset which looks like this:
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Markov Process and transition matrix
I would like to find some good courses but also a quick response on how to model transition matrix given the states.
Imagine having 4 states and the following array [1,2,4,1,3,4,2 etc etc]. What ...
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Hidden Markov Models: Best practices in selecting observable variables
I am just getting started with Hidden Markov Models. In selecting my observable variables, there are some where I believe the recent change in the variable is potentially more predictive than its ...
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Likelihood of a hidden Markov model does not increase in case of multidimensional data
I am implementing a HMM (Hidden Markov Model) for time series data to assess (define) the state of the model at each time period (with continuous observations). To maximize the likelihood of the model ...
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Modeling heterogeneous data with a HMM
I have gone through the concepts of HMM and I have understood most of them. However, I'm confused about how to map it to my problem.
I have patients' information. Each patient is delivered a medicine ...
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Suggestions for studying *Clickstream* data
I've essentially been handed a dataset of website access history and I'm trying to draw some conclusions from it.
The data supplied gives me the web URL, the datetime for when it was accessed, an the ...
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Hidden Markov Model
I am trying to find answers to the following questions. Can someone please help. This is a Hidden Markov Model with 7 states and 4 observations. I have worked out the following solution but still need ...
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How do I initialize a Hidden Markov Model when using MFCC features for speech recognition?
I have a personal dataset of 10000 audio files, each consisting a single spoken sentence. These files each have the transcribed text labels with them that I can use for supervised HMM training.
Now ...
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Which latent variable model is better to find hidden variable?
Currently, I am exploring the concept of latent variable for regression type datasets.
I have gone through literature of few of ...
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global independence vs local independence in markov network
I could not understand the local independence and global independence of a markov network.
Please help me understand with a simple graph
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Clustering similar sequences using hidden markov model
I have several sequences of different lengths. For example,
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How do I test and validate a Markov Model in RStudio?
I've created a Markov Model in RStudio using the seqHMM library. I'm new to R and would usually do this kind of thing in Python, but I wanted to use seqHMM. I can see the model has been created and it ...
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Comapring hidden markov models
Given a set of sequence transitions, there are different orders of hidden markov models that can be fitted to a dataset.
Is there any test to determine which is the best model for a given sequence ...
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Is there HMM that looks two elements back?
The original HMM model looks only one element back (considers only previous state). Sometimes it viable to look two elements back. Is there an extension to HMM that allows that?
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Hidden Markov Model: Forward Algorithm implementation in Python
I am learning Hidden Markov Model and its implementation for Stock Price Prediction. I am trying to implement the Forward Algorithm according to this paper.
Here I found an implementation of the ...
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Regime detection to identify transitions between habitats
The following figure represents the concentration of a substance (referred to as Element in the code) measured in an organism throughout its life. There are ...
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Hidden Markov Model with Autoregressive emission model?
So far, all standard HMM implementations I've seen assume some variation of a Gaussian Mixture (GMM) as their emission model. It can of course only have a single mixture component which reduces it to ...
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GMM in speech recoginition using HMM-GMM
I am trying to solve/understand ASR using HMM-GMM.
At the abstract level i do understand what's happening but I did not
understand how GMM fits into it.
My data has 5K hours of speech from single ...
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How can I know the method that HMM use to choose the hidden states automatically?
As I know, I can just decide the number of hidden states, then put my observations fit into my HMM model, the model will generate the hidden states for me.
I am really curious how it does work. Can ...
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Intuition behind the RNN/LSTM hidden state?
What's the intuition behind the hidden states of RNN/LSTM? Are they similar to the hidden states of HMM (Hidden Markov Model)?
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Best HMM Package
What is the best HMM (Hidden Markov Model) library available in Python? I have already looked into seqlearn and hmmlearn, but both of them don't seem to be actively maintained.
Thanks in advance!
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Best python library for training using Hidden Marov model with Gaussian Mixture
I would like to train my data using HMM- GMM (Baum Welch approach with gaussian Mixture) to find the best parameters suited for my data.
Note : My data is ...
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Does feature normalization improve performance of Hidden Markov Models?
For training a Hidden Markov Model (HMM) on a multivariate, continuous time series, is it preferable to scale the data somehow? Some pre-processing steps may be:
Normalize to 0-mean and unit-variance
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predicting next observation using HMMLearn.multinomialhmm(discrete hmm)
I have implemented a HMM using hmmlearn:
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Code or Package to cluster sequences (or time series) of different lengths based on HMM?
Is there any existing code or packages in Python, R, Java, Matlab, or Scala that implements the sequence clustering algorithms in any of the following 2 papers?
1) 'Clustering Sequences with Hidden ...
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Statistical machine translation word alignment for FR-ENG and ENG-FR: what is p(e) and p(f)?
I'm currently trying to implement this paper, but am struggling to understand some of the math here. I'm pretty sure I understand how to implement the E-step, but for the M-step, I'm confused on how ...
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HMMLearn Predict Next Observed Event
From my understanding you can use the transition matrix to predict the probability of going from the last predicted hidden state(state t), to the t+1 hidden state. My confusion is how in code format ...
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Why are observation probabilities modelled as Gaussian distributions in HMM?
HMM is a statistical model with unobserved (i.e. hidden) states used for recognition algorithms (speech, handwriting, gesture, ...). What distinguishes DHMM form CHMM is the transition probability ...
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Unequal length observation sequences when training Hidden Markov model
I want to train a sequence classifier with Hidden Markov Model. The length of observation sequences is not fixed. I tried some HMM packages such as Matlab's HMM toolbox and Kevin Murphy's library. All ...
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What is the complexity of Mixture Hidden Markov Models (MHMM)?
I wonder what is the theoretical computational complexity of MHMM.
Is it related to the number of alphabets in sequence mining?
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How to set the parameters of a Hidden Markov Model that'll be used to correct the mistakes by a previous classifier?
Say we've previously used a neural network or some other classifier C with $N$ training samples $I:=\{I_1,...I_N\}$ (that has a sequence or context, but is ignored by C) the, belonging to $K$ classes. ...
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depmixS4 - How to fit HMM usgin multiple sequences of observation
Is there any R package that supports fitting an HMM using multiple sequences of observations? to the best of my knowledge depmixS4 does not support this feature
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Markov Chains for sequential data
I am new to Markov chains and HMM and I am looking for help in developing a program (in python) that predicts the next state based on 20 previous states (lets say 20 states in last 20 months). I have ...
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Hidden Markov Model on R Studio
Is there any detailed materials that can help explain how to set up HMM on R Studio?
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