# Questions tagged [naive-bayes]

The tag has no usage guidance.

52 questions
0answers
12 views

1answer
28 views

### How is the right term derived in this conditional probability statement?

Does anyone know how to get the right term? It seems like the right term is actually $P(C, x_1, x_2, \ldots, x_n)$ and not $P(C \mid x_1, x_2, \ldots, x_n)$?
1answer
196 views

1answer
857 views

### Interpreting the results of a Naive Bayes classifier.

Using the Naive Bayes formula to classify text I have something like... $$P(Cat|Word1) = \frac{P(Word1|Cat) * P(Cat)}{P(Word1)}$$ Using a small example ... ...
1answer
382 views

### Naïve Bayes Classifier

For the Data Mining - Naïve Bayes Classifier for the case of "Numberless values for an attribute", the conditional probability is modeled with the normal distribution (see below). Probability Density ...
1answer
73 views

### Bayesian Nets and weird probability

I have to solve the following problem: Suppose we have a bayesian net in which we have the following variables: R, PA and PR Let: P(R) = 0.1, P(PA) = 0.5, P(PR|R, PA) = 0.6, P(PR|¬R, PA) = 0.4, P(...
1answer
29 views

### Probability with a joined condition

I want to know the probability $P(A|X,Y)$, given that I know $P(A|X)$, $P(A|Y)$, $P(A)$, $P(X)$, $P(Y)$ and given, that $X$ and $Y$ are independent. I'm also going to assume that $X$ and $Y$ are ...
1answer
310 views

### Bernoulli Naive Bayes Classification

I am having trouble understanding the following text regarding Bernoulli Naive Bayes. Specifically, the author mentions that $i$ is a feature. However, what is the difference between $x_i$ and $i$?
1answer
95 views

### How to solve conditional probability problem using bayesian algorithm

I am trying to solve An agent learning to categorise news articles in two topics, World (W) and Finance (F). Out of $100$ articles, $40$ were classified as W, and $20$ of the articles were ...
1answer
58 views

### What assumptions did I make when I strengthened my independence criterion across a new random variable?

I have an algorithm which tries to calculate some $\operatorname{Pr(X | Y_1 Y_2 \dots )}$ (where juxtaposition means event intersection, "given $Y_1$ and $Y_2$ and ... have happened".) We have some ...
0answers
131 views

### The significance of odds and logs in Bayes Naive Classification

I do understand the concept of Naive Bayesian classification, as it tries to calculate the probability of an outcome of a class given multiple evidences. It comes from the Bayes theorem and it is ...
1answer
701 views

### Naive Bayes: Conditional Independence vs. Marginal Independence Assumption

Apologies if this question would rather belong on Stat SE. I am following Kevin Murphy's tutorial A brief introduction to Bayes' Rule. I seem to follow his derivations formally, but my intuition in ...
1answer
80 views

### Translation:Bayes Classificator -> precise math?

I want to understand the most simple form of the Bayes classificator (see here) but I want to understand it in a really precise, clean, mathematical way. Math description of the setting: Let us ...
1answer
255 views

### Trouble understanding how Naive Bayes Classifier is derived

I've come across the Naive Bayes Classifier while studying machine learning, but the trouble I'm having is with some of the probability theory used to derive the formula for finding the optimal ...
1answer
1k views

### Cluster probabilites: Bayesian network (sprinkler example, Russel/ Norvig) as a clustered network

like others here I am also learning with Russel's and Norvig's book about artificial intelligence. My question is about the conditional probability tables of a clustered multiply connected network ...
2answers
852 views

### Conditional probability of C given two independent events

Suppose that a machine depends on the working state of two components A and B. If both $A$ and $B$ do not function then the probability (say $C$) of the machine to work is $0.3$ If both $A$ and $B$ ...
0answers
289 views

0answers
401 views

### Interpretation of MATLAB's NaiveBayses 'posterior' function

After we created a Naive Bayes classifier object nb (say, with multivariate multinomial (mvmn) distribution), we can call ...