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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.

Hidden Markov Models (HMM) are a model for understanding and predicting sequential data in statistics and machine learning, commonly used in natural language processing and bioinformatics. In HMM, the hidden state variable cannot be observed, but usually some output variable that dependent on the hidden state is visible.

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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 do I go from the hidden state predicted at time…
Femi
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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!
Edamame
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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 matrix P with elements. In CHMM, state space of…
Roberto Pierson
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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 a sequential dataset with 50 customers i.e. the…
mlgal55
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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 help with parts ii & iii. Solution: I. GATTAG =…
Maninder Preet Singh Puri
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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 the methods and models used in finding latent variable, like: EM algorithms, Partial least square regression, Latent…
Mohammad Saad
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Clustering similar sequences using hidden markov model

I have several sequences of different lengths. For example, Seq1 -- "A", "B", "A", "A", "K", "L", "C", "B","C", "D" Seq2 -- "A", "C", "A", "D", "C", "A", "K", "D" Seq3 -- "B", "C", "A", "A", "B", "K", "A", "D", "L", "A",…
Bloodstone Programmer
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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 set? How to compare two HMM fitted on to a sequence…
APaul31
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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 Forward Algorithm in Python. import pandas as…
Joe Rakhimov
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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 several distinct regimes in the data that correspond with this organism moving in and out…
Ryan
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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 user. I took the above picture from this article. I…
Naveen Gabriel
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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 anyone explain the calculation or share the link…
Kinglun Poon
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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 Scale to [-1, 1] interval Scale to [0, 1]…
hazrmard
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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 to compute the M-step. It says just before section…
mudkipium
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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
user3607644
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