# Questions tagged [bayesian-statistics]

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### SMO, Random forest and Bayes net algorithms: why does Random forest perform better?

I analyzed a dataset using those 3 different algorithms. As I can see, Random forest performs better in most cases. My dataset is composed of 4000 instances of two classes (class A 2000 elements, ...
34 views

### What is the time complexity of the SGVB estimator?

In the context of variational autoencoders, we want to maximize the evidence lower bound and this is typically done using Stochastic Gradient Variational Bayes (SGVB). I was curious if there is any ...
50 views

### Density of uniform distribution over two disjoint squares

A probability distribution $P$ over $X \times \{0, 1\}$. $P$ can be defined in term of its marginal distribution over $X$ , which we will denote by $P_X$ and the conditional labeling distribution, ...
39 views

### Gaussian distribution with condition?

What does this expression mean? Normal distribution with condition I am reading a research paper and found the following expression (Eq.28 in the paper below). It means a Gaussian distribution, but ...
53 views

### how many parameters do we need to estimate for a general probabilistic model

Its a question from a test in machine learning. I have 3 binary variables x1,x2 and x3 (which means that each one of them can be either 1 or 0), each one of them has a binary output y (can be 0 or 1). ...
84 views

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### Not grasping Bayesian Monte Carlo

I've read several sources of information that describe the process of Bayesian Monte Carlo Quadrature but am just not understanding the details enough to be able to implement it. For instance two ...
33 views

### Unsupervised learning: necessity of labels and dependency between features and labels?

I have logs of activities without labels, which describe whether an activity is normal or not. Assuming that normal behaviors will follow a Gaussian distribution, I fit Gaussian distributions on ...
11k views

### What is meant by the term “prior” in machine learning

I am new to machine learning. I have read several papers where they have employed deep learning for various applications and have used the term "prior" in most of the model design cases, say prior in ...
317 views

### Convergence of Markov model

I was learning Hidden Markov model, and encountered this theory about convergence of Markov model. For example, consider a weather model, where on a first-day probability of weather being sunny was 0....
347 views

### Are the Confabulation Theories of Thaler and Hecht-Nielsen Isomorphic?

Both S. L. Thaler and R. Hecht-Nielsen have set forth neural-based theories of "confabulation" applicable to machine learning. The essential mathematics of Hecht-Nielsen is set forth in his paper "...
48 views

### Using counting to build a grid world

For this question, I have tried everything that I can think of, but cannot solve it. What I want to do is iterate over all possible values of $z_1$, but every method I use, it requires me to know ...
44 views

### What ML methods exist to categorize signal from noise? Red noise? Spatially correlated noise?

Let's say we are given measurements of some sort. In many cases, it is safe to assume that noise is white noise, serially uncorrelated, and zero mean with some finite variance. But in other cases, ...
154 views

### Variable elimination in Bayesian network

I'm trying to check if my understanding of variable elimination is correct. Assume the above Bayesian network is factorized as: $p(a,b,d,e,l,s,t,x) = p(a)p(t|a)p(e|t,l)p(x|e)p(l|s)p(b|s)p(d|b,e)p(s)$...
383 views

### Expectation Maximization Algorithm for simple naive Bayesian network

I am trying to understand the following network A has two children - B & C (aka common cause) All the variables are binary and can be either 0 or 1. In data values are missing only for some ...
36 views

### How can a distributed system cooperate to determine rules of its environment?

I'm sorry if this question is silly or elementary. I'm not a computer scientist so I don't know the vocabulary to use to ask this question. Thus I've produced an analogy to explain the challenges I'm ...
61 views

### Simple Bayesian classification with Laplace smoothing question

I'm having a hard time getting my head around smoothing, so I've got a very simple question about Laplace/Add-one smoothing based on a toy problem I've been working with. The problem is a simple ...
52 views

### Why naive Bayes performs better?

I have found that naive Bayesian classifier performs much better than classification using mixture of multivariate Gaussians. Here is the problem: I have a set of objects with attached features (10 ...
1k views

### Difference between Bayesian Networks and Dynamic Bayesian Networks

I'm studying Bayesian networks and want to clarify a couple of things with people who are more knowledgable in the area than me. As far as I understand it, a Bayesian network (BN) is a directed ...
736 views

### Approximate Bayesian Computation VS Monte Carlo Simulation

I am a little confused about the differences between Approximation Bayesian Computation (ABC) and Monte Carlo Methods (MCM). Citing from wikipedia: Approximate Bayesian computation (ABC) constitutes ...
302 views

### Bayesian Nets & Markov Blanket

As i passed PHD entrance exam, some days ago, i want to find solutions for challenging problem. In Bayes network on X={X1,...Xn} each random variable has P parents and Q child's. for Xi we want to ...