Tagged Questions

3
votes
2answers
31 views

Naive Bayes feature probabilities (Do I double count words?)

I'm prototyping my own Naive Bayes bag o' words model, and I had a question about calculating the feature probabilities. Let's say I've got two classes, I'll just use spam and not-spam since that's ...
1
vote
1answer
53 views

Find out the conditional probability

Consider I have the following probabilities: $$P(A|B) = 0.86 $$ $$ P(A|B^C) = 0.35 $$ $$ P(B) = 0.80 $$ $$ P(A) = 0.758$$ Is there necessary information given to calculate $P(B^C|A^C)$? If so ...
2
votes
0answers
42 views

Using probability scores from a random forest

I've the following problem. I've a data set that tries to predict whether a given buy event will happen or not (0/1) when a customer sees a certain product, and I've features created for both the ...
-1
votes
1answer
147 views

Calculating conditional probabilities given a bivariate gaussian

This is a continuation of my previous question. I have two classes, $C_1$ and $C_2$. $C_1$ is a bivariate Gaussian with mean $\mu = (0,0)$ and covariance $\Sigma = I$ $C_2$ is a bivariate ...
0
votes
1answer
85 views

Moralization and triangulization on belief networks

Assume that I have a belief network with a set of nodes. In order to create a valid junction tree I have to moralize the graph. Assume now that I have nodes with more than 2 parents (e.g 3 parents) ...
5
votes
2answers
189 views

Bayes' Theorem - Probability Pants problem

I'm having an issue with a question regarding Bayes' Theorem. Here is the question: An online clothing store carries three brands of jeans. 40% of sales are brand A, 20% are brand B and the ...
1
vote
0answers
26 views

Constructing a model from multiple non-independent and unreliable predictors?

I have an interesting modelling problem in which I am trying to forecast the occurrence of a type of weather event using an empirical model driven by measurements of a number of different physical ...
5
votes
1answer
196 views

Confidence intervals when using Bayes' theorem

I'm computing some conditional probabilities, and associated 95% confidence intervals. For many of my cases, I have straightforward counts of x successes out of ...
2
votes
1answer
117 views

Is Perkins et al.'s “skill score” an application of Bayes' theorem?

Perkins et al. (2007) introduce a "skill score" for measuring climate model output against observations. The score basically consists of measuring the overlap between probability density functions of ...
2
votes
1answer
380 views

How to calculate joint probabilities from conditional probabilities in a Bayesian Network?

This question is about Bayesian Networks. I want to calculate the probability for certain events to be in a certain state knowing all conditional probabilities. Consider that I am totally new to ...
4
votes
1answer
98 views

Time-wise treatment effect / survival analysis

Let's say I have some kind of survival data - i.e. I'm giving a drug that may cause mortality. So I have three patients: A, B and C. All are given the drug at Time t1. Let's say patient A dies at ...
2
votes
3answers
160 views

Confused about relevance of Bayes' theorem to my problem

I've spent the morning teaching myself about Bayes's theorem, because I assumed that it was required to help me solve my problem. However, the answer I've ended up with is the same as I would have got ...
6
votes
4answers
557 views

Derive P(C | A+B) from Cox's two rules

I am working my way (self-study) through E.T. Jaynes' book Probability Theory - The Logic of Science Original Problem Exercise 2.1 says: "Is it possible to find a general formula for $p(C|A+B)$ ...
3
votes
2answers
117 views

What techniques are used for empirical, stochastic simulation of a time series?

Suppose you have recorded a set of paths in the $y,t$ plane, with $y = f(t)$, $f$ is a stochastic function (i.e. there is a noise term), and $t$ might be time or some other monotonic increasing ...
0
votes
1answer
458 views

How to calculate conditional & marginal probability for both the positive and negative hypotheses?

Sorry to keep bothering you guys with this thing, but another stupid question: Given the following data (from my previous question), how would one calculate the conditional probability and marginal ...
1
vote
3answers
1k views

Bayesian probability > 1 — is it possible?

Running a crude model using Bayesian inference, I get some results > 1 (ie, more than 100% "certain") for some combinations of "evidence". For instance, for one bit of evidence the conditional ...
1
vote
3answers
821 views

Bayes Network computing conditional probabilities

There is a bayesian network Asia: I am computing based on ...
2
votes
2answers
270 views

Decision network example

I am reading this example, but could you explain a little more. I don't get the part where it says "then we Normalize"... I know ...
3
votes
2answers
571 views

Specifying conditional probabilities in hybrid Bayesian networks

I am trying to get a deeper understanding of the various types of Bayesian networks. Most of the literature/lectures I've come across use discrete random variables exclusively and only mention ...