For questions related to the naive Bayes, which is a machine learning (or statistics) technique that is based on the Bayes' theorem.
See e.g. https://en.wikipedia.org/wiki/Naive_Bayes_classifier for more info.
Questions tagged [naive-bayes]
23 questions
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What are the main differences between a perceptron and a naive Bayes classifier?
What are the main differences between a perceptron and a naive Bayes classifier?
user3642
6
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1 answer
Why is the denominator ignored in the Bayes' rule?
The naïve Bayes' generative algorithm is often represented by the following formula:
$$\text{argmax}_{y} p(y|x) = \text{argmax}_y \frac{p(x|y)p(y)}{p(x)} \approx \text{argmax}_y p(x|y)p(y)$$
Why do we have $p(x)=1$ which allows the approximation…
gcorso
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$\frac{P(x_1 \mid y, s = 1) \dots P(x_n \mid y, s = 1) P(y \mid s = 1)}{P(x \mid s = 1)}$ indicates that naive Bayes learners are global learners?
I am currently studying the paper Learning and Evaluating Classifiers under Sample Selection Bias by Bianca Zadrozny. In section 3. Learning under sample selection bias, the author says the following:
We can separate classifier learners into two…
The Pointer
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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 $P(x_i \mid Y=y_k) \sim \mathcal{N}(\mu, \sigma^2)$ is a Gaussian distribution.
In order to…
imflash217
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4
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Why would LDA have performed much better than SVM and Naive Bayes in diagnosing ADHD?
In a final project in diagnosing Attention deficit hyperactivity disorder (ADHD) using Machine Learning, we obtained parameters from real patients. We used this data and got much higher success rates with LDA than with SVM and Naive Bayes. We had…
roi mal
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3
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Why is my calculation of the probability of an object being in a certain class incorrect?
In the attached image
there is the probability with the Naive Bayes algorithm of:
Fem:dv/m/s Young own Ex-credpaid Good ->62%
I calculated the probability so:
$$P(Fem:dv/m/s \mid Good) * P(Young \mid Good)*P(own \mid Good)*P(Ex-credpaid \mid…
TomaateTip
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3
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2 answers
Doesn't every single machine learning classifier use conditional probability/Bayes in its underlying assumptions?
I'm reading about how Conditional Probability/ Bayes Theorem is used in Naive Bayes in Intro to Statistical Learning, but it seems like it isn't that "groundbreaking" as it is described?
If I'm not mistaken doesn't every single ML classifier use…
Katsu
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1 answer
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 order to build a classifier to identify the…
Eric Schwarz
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3
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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 networks for small dataset problems.
jennifer ruurs
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3
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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 $c$ is the class the model may classify $y$ as.
And…
Shrike Danny
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2
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1 answer
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 not. I'd the probabilities to be in the interval…
Yacine al
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2
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How can I apply naive Bayes classifier for three classes (Positive, Negative and Neutral) in text data?
I found a naive Bayes classifier for positive sentiment or a negative sentiment Citius: A Naive-Bayes Strategy for Sentiment Analysis on English Tweets. But with most available datasets online, sentiments are classified into 3 types: positive,…
Md. Asif Iqbal Fahim
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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 purpose is to reduce variance. Naive Bayes has…
Sivaram Rasathurai
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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, plug the parameters and calculate the "Likelihood…
Soumee
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My Gaussian Naive Bayes classifier is too slow
I am trying to build a film review classifier where I determine if a given review is positive or negative (w/ Python). I'm trying to avoid any other ML libraries so that I can better understand the processes. Here is my approach and the problems…
Ayumu Kasugano
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