Skip to main content

Questions tagged [naive-bayes-algorithim]

0 votes
1 answer
92 views

I need to understand, how multinomial-naive-bayes can make prediction based on scikit-learn implementation. I saw the source code but I want to understand the math behind it. Could you please explain ...
Mahdi Amrollahi's user avatar
0 votes
2 answers
924 views

These past days, in college, we have been learning about NaiveBayes. Since it's a classification algorithm, I was wondering if I could evaluate NaiveBayes models the same way (using the same metrics) ...
ilved17's user avatar
  • 41
0 votes
2 answers
110 views

I have run some data on the possibility of churn in a telecom company based on 6 variables How now do I interpret the output below for the probabilities:
Brandon 's user avatar
1 vote
2 answers
949 views

I am working on implementing a Naive Bayes Classification algorithm. I have a method def prob_continous_value which is supposed to return the probability density ...
Evan Gertis's user avatar
0 votes
1 answer
2k views

The sci-kit learn library by defaults provides two options either no stop words or one can specify stop_words=english to include a list of predefined English words I am using Naive Bayes for SMS spam ...
Juan's user avatar
  • 15
1 vote
1 answer
110 views

There are various types of Naive Bayes algorithms in the Sklearn library: Can all of them be used for text classifications? And which one's perform bette I tested out a simple text classification ...
Juan's user avatar
  • 15
2 votes
0 answers
157 views

I've been using Orange for a while to rapidly prototype a few classification models. One of the ones I've been using is 'Naive Bayes'. If I understand correctly, there are a few types available based ...
Cranialsurge's user avatar
2 votes
1 answer
950 views

Naive Bayes classifiers have the following characteristics-: They are robust to isolated noise points because such points are averaged out when estimating contiditional probabilities from data. Naive ...
achhainsan's user avatar
1 vote
2 answers
468 views

How do we know if your features in my dataset are independent before applying Naive Bayes? Basically I want to know is it possible for us to get an idea before training our model if Naive Bayes will ...
smsubham's user avatar
0 votes
1 answer
80 views

In the Positive Negative Sentiment Analysis, Would it make sense mathematically to instead of keeping a score of the positive frequencies and negative frequencies of a word, calculate the difference ...
Rockko Rock's user avatar
2 votes
1 answer
2k views

I am having some difficulties in improving results from running a Naive Bayes algorithm. My dataset consists of 39 columns (some categorical, some numerical). However I only considered the main ...
Math's user avatar
  • 161
5 votes
1 answer
604 views

Some articles say that naive Bayes is naive because of "independence of attributes". Whereas others say "independence of attributes within a class". Can anybody please clear this ...
satinder singh's user avatar
1 vote
1 answer
61 views

Naive Bayes algorithm used for text classification relies on 2 assumptions to make it computationally speedy: Bag of Words assumption: the position of words is not considered Conditional Independence: ...
Darcey BM's user avatar
  • 197
1 vote
3 answers
910 views

I had used TfidfVectorizer and passed it through MultinomialNB for document classification, It was working fine. But now I need to pass a huge set of documents for ex above 1 Lakh and when I am ...
Rajesh das's user avatar