Questions tagged [naive-bayes-algorithim]
The naive-bayes-algorithim tag has no usage guidance.
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Implementing Complement Naive Bayes for continuous data?
I'm looking to implement the Complement Naive Bayes algorithm for my continuous features. For the Gaussian technique I have calculated the normal distribution per feature x class, however what's the ...
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How Naive Bayes makes prediction based on scikit-learn?
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 ...
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Does it make sense to build a ROC curve for Naive Bayes classification?
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) ...
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Explaining Probabilities in Python with Naive Bayes
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:
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How to calculate true positive, true negative, false positive, negative and postive with Bayes Classifer from scratch
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 ...
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Stop words list to use for CountVectorization
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 ...
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Comparison of different Naive Bayes algorithm for SMS classification
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 ...
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What type of 'Naive Bayes' algorithm is provided by Orange?
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 ...
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Really confused with characteristics of Naive Bayes classifiers?
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 ...
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Independence of Features assumption in Naive Bayes
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 ...
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Subtraction of Positive and Negative Frequencies in Sentiment Analysis
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 ...
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How to improve results from a Naive Bayes algorithm?
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 ...
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Why naive bayes is "naive"
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 ...
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How does the Naive Bayes algorithm function effectively as a classifier, despite the assumptions of conditional indpendence and bag of words?
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:...
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How to implement HashingVectorizer in multinomial naive bayes algorithim
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 ...
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