Questions tagged [naive-bayes]

For questions related to the naive Bayes, which is a machine learning (or statistics) technique that is based on the Bayes' theorem.

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7 views

How to make specific test data prediction with fitted GaussianNB Classifier in Python

I'm trying to make news classification. Here is the neural network: ...
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21 views

Why don't ensembling, bagging and boosting help to improve accuracy of Naive bayes classifier?

You might think to apply some classifier combination techniques like ensembling, bagging and boosting but these methods would not help. Actually, “ensembling, boosting, bagging” won’t help since their ...
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Are there any examples of state-of-the-art NLP applications that are still n-gram based and use Naive Bayes?

As far as I can tell, most NLP tasks today use word embeddings and recurrent networks or transformers. Are there any examples of state-of-the-art NLP applications that are still n-gram based and use ...
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How can the expectation-maximization improve the classification?

I am learning the expectation-maximization algorithm from the article Semi-Supervised Text Classification Using EM. The algorithm is very interesting. However, the algorithm looks like doing a ...
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1answer
62 views

Understanding how to calculate $P(x|c_k)$ for the Bernoulli naïve Bayes classifier

I'm looking at the Bernoulli naïve Bayes classifier on Wikipedia and I understand Bayes theorem along with Gaussian naïve Bayes, however when looking at how $P(x|c_k)$ is calculated I don't understand ...
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What is the meaning of test data set in naive bayes classifier or decision trees?

What is the benefit of a test data set, especially for naive bayes estimator or decision tree construction? When using a naive bayes classifier the probabilities are a fact. As far as I know there is ...
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44 views

Why do Bayesian algorithms work well with small datasets?

I read very often that Bayesian algorithms work well on small datasets. Why is that? I think it is because they might generalize more, but why is that? See also Investigating the use of Bayesian ...
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83 views

How to build naive bayes graph from data

For an university assignment I have to use the HuginLite software to do some probabilistic inferences with different algorithms. One of these algorithms is Naive Bayes but its graph is not built ...
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1answer
127 views

What to do when PDFs are not Gaussian/Normal in Naive Bayes Classifier

While analyzing the data for a given problem set, I came across a few distributions which are not Gaussian in nature. They are not even uniform or Gamma distributions(so that I can write a function, ...
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124 views

What is the relationship between MLE and naive Bayes?

I have found various references describing Naive Bayes and they all demonstrated that it used MLE for the calculation. However, this is my understanding: $P(y=c|x)$ $\propto$ $P(x|y=c)P(y=c)$ with $...
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1answer
97 views

Why do I get small probabilities when implementing a multinomial naive Bayes text classification model?

When applying multinomial Naive Bayes text classification, I get very small probabilities (around $10e^{-48}$), so there's no way for me to know which classes are valid predictions and which ones are ...
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294 views

Why is the denominator ignored in the Bayes' rule?

The naive Bayes' generative algorithm is often represented by the following formula $$\text{argmax}_{y} p(y \mid x) = \text{argmax}_y \frac{p(x|y)p(y)}{p(x)} \approx \text{argmax}_y p(x|y)p(y)$$ Why ...
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388 views

Is logistic regression more free from the conditional independence assumption than naive Bayes?

To my understanding, logistic regression is an extension of naive Bayes. Suppose $X = \{x_1, x_2, \dots, x_N \}$ and $Y = \{0, 1\}$, each $x_i$ is i.i.d and $P(x_i \mid Y=y_k) \sim \mathcal{N}(\mu, \...
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153 views

What is the most effective way to build a classifier?

At the moment, I am working on a project which requires me to build a naive Bayes classifier. Right now, I have a form online asking for people to submit a sentence and the subject of the sentence, in ...