Questions tagged [markov-process]

A Markov process is a stochastic process for which the Markov property holds: If you know the current state, then the next state is independent of all past states.

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Comparing transition matrices for Markov chains

I have a population, each unit of which exists in one of several states that change over time. I am using first-order Markov chains to model these state transitions. My population can be segmented ...
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If I use Gibbs sampling with a Bayesian model, what do I have to check is memoryless?

Right now I am trying to better understand how Bayesian modeling works with just the basics. I found through reading tutorials that some very basic Bayesian models like Bayesian Hierarchical Modeling ...
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Identifying sequences of behavioral interactions between multiple individuals

I'm wondering if anyone might have some novel insights as to the best way to analyze the following data. It's a problem I've been thinking about in the back of my mind for a while, so I thought that ...
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"Learning" algorithm to use when future depends on past events (MDP property not met)

There are around 5 different retirement plans available in my country. People can pick from them freely. I would like to create a solution that would try to predict the best plan(s) given a particular ...
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220 views

How to use HMMs for continuous value prediction

I have some time-series data, which I need to use to predict a continuous value for a given time-stamp. I was initially doing it using a Multivariate Regression Model but I later figured that a time-...
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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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25 views

state transition classification on terminal state

I have data on a unit $i$ which enters an entry state $S_0$. This unit has some covariates $x_i$ I would like to predict the probability the unit will reach the terminal state $S_{pos}$ or $S_{neg}$. ...
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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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Ranking graph's nodes by score propagation

Problem I have the following directed tripartite graph $G(E\cup V\cup P, A)$, where there is a many-to-one symmetric relationship between the subsets V and E - $e\in E,v\in V,[e, v]\in A \iff [v, e]\...
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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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23 views

Estimating model for transition probabilities of a Markov Chain

Suppose that I have a Markov chain with $S$ states evolving over time. I have $S^2\times T$ values of the transition matrix, where $T$ is the number of time periods. I also have $K$ matrices $X$ of $T\...
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Reinforcement learning - generating a matrix of continuous values with varying size for test data generation

Currently, I am using RL A3C algorithm for test data generation, where for a set of 30 functions written in C (mostly basic algorithms like Prime number checks, triangle validity, etc.) I try to ...
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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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Markov chain modelling?

I am working on a personal loan dataset. For each loan, we recorded its credit status monthly after it was drawn by the borrower. Let's say there were 6 status coded by A-F. My project is to use ...
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276 views

Online methods for sequence prediction

A ml beginner here, so please bear with me. If I understand correctly RNNs seem to be the go to method right now for sequence prediction for a given input (single/as a sequence). But I do not have ...
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Deciding on sequence prediction approach

I have a space of 128 states expressed with binary bitstrings. The transition probabilities among these states are known to me, as follows: ...
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Multi Agent Reinforcement Learning

I am trying to build multi agent reinforcement learning in 2D grid environment(Combat & Switch) using OpenAI. When I am trying to build game using ten agents, five opponents and the dimension is(...
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Find changes in variables into two states

I have a dataframe like this: ...
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21 views

Machine Learning alternative for hashing

Is there a Machine Learning technique that can used to detect the slightest change in data? I know this can be done using a hash but I was just wondering if there is any machine learning technique out ...
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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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2answers
80 views

Machine Learning algorithm for detecting anomalies in large sets of events

Let's start with the following hypothetical preconditions: There is traffic: normal and anomaly. Each traffic sample contains a list of events (of variable size) Events happen in order, the possible ...
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Simple Markov Chains Memoryless Property Question

I have a sequential data from time T1 to T6. The rows contain the sequence of states for 50 customers. There are only 3 states ...
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521 views

HMM - Matlab for data set to detect anomaly

I have a dataset of oil temperatures. The time series consist of 100 hours of measurement at every second. There is an anomaly in the data that I would like to detect using Hidden Markov Models (HMM). ...