A naive Bayes classifier is a simple probabilistic classifier based on applying Bayes' theorem with strong independence assumptions. A more descriptive term for the underlying probability model would be "independent feature model".

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Text Classification using TfIdf and Bernoulli NB

So, as I am reading about Bernoulli distribution and text classification, I want to understand how Bernoulli uses TfIdf features? Since TfIdf values are within [0-1) but Multivariate Bernoulli assumes ...
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Which model to predict air cleanness (air pollution) in daily-basis? [on hold]

How hard it is to predict air pollution? My friend is an agronomist: he is doing some research on some small plants. The plants are very sensitive to air pollution in urban areas [need deep ...
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7 views

Define feature for text classification using NLTK [on hold]

I'm working on Aspect Based sentiment analysis , I have a training set (text ,and aspectTerms) for each review. Using NLTK , I wan to build a NaiveBays Classifier that predict aspects of test unseen ...
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294 views

Request: Clever Things to do with Naive Bayes

I am trying to drive up the performance of a Naive Bayes classifier, and I haven't been having terribly much luck. I've been working in Weka, but have enough knowledge of R to (possibly) implement ...
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15 views

Decision function for BernoulliNB classifier. ( for use in plotting ROC and PR curves )

I would like to plot the PR curve using scikit-learn for the Bernoulli Naive Bayes estimator. However, attempting to do so give an error, ...
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Explanation for large difference in SVM and Naive bayes results

I have a dataset with 389 data evenly distributed into 6 classes. Each data has 1024 features. So my dimension is much larger than my observation data. I have tried to see some common classifiers on ...
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35 views

Naive Bayes Nearest Neighbor (NBNN) implementation problems in MATLAB

I'm currently trying to classify the CIFAR-10 image dataset. I cam across a number of papers praising the the results from a non-parametric approach called Naive Bayes Nearest Neighbors. It uses SIFT ...
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Alternatives to Non-Linear Regression

I'm not a professional statistician but I frequently work in the area of data analysis using R and Python, and frequently use linear regression models (OLS) or quantile regression, and tree based ...
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49 views

Balanced datasets in Naive Bayes

In a classification model, it is well known that a desirable situation is that all possible classification classes are evenly represented in the training dataset. Datasets that satisfy this property ...
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26 views

Biasing SkLearn Algorithms to Positive Outcomes

I am trying to run multinomial naive bayes on a series of examples in python using sci kit learn. I am consitently getting all examples classified as negative. (The ratio of positives to negatives in ...
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fragmentation problem in decision tree

I am taking a NLP class, in which it says decision tree has the fragmentation problem. It says ...
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46 views

How to prepare a dataset for text classification

I would like to compare some algorithms for performing sentiment classification (Naive Bayes, SVM, and ...
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31 views

define prior probabilities in naive bayes with unbalanced classes and asymetric cost

I'm trying to apply Naive bayes to the following supervised problem: It's a binary classification problem The classes are unbalanced. The target class represents the 0.004266432 of the total and the ...
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6 views

making for making dataset for spam classifier [on hold]

I'm trying to make a dataset for spam detection, what is the best automatic selection that I can use for picking up the word that should i count for my spam base ? Thank you
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My naive bayes classifier doesn't show probabilities [duplicate]

I'm trying to predict the probability between 1-0 and have found that naive bayes is supposed to show this, however when I use it I only have ...
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2answers
106 views

Can $p(Y|a,b)$ ever be equal to $p(Y|a) \cdot p(Y|b)$?

This strikes me as a simple question, but in re-visiting how the Naive Classifier works I started wondering if there is any probabilistic model that under certain independency assumptions obtains: ...
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21 views

Naive Bayes Produce Confidence

I am pretty newbie in machine learning. Please forgive and point out anyone incorrect use of terminology. Now I am learning Naive Bayes algorithm. As I have learned Neural Network, when predicting, ...
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38 views

Naives Bayes example walk through

My instructor have give me an example that I didn't really understand, can someone help me in understanding it? Given a list of occupation and a list of grocery bought I want to recommend a list of ...
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23 views

Regarding Naive Bayes and conditional independence

We all have been talking about how Naive Bayes may, in some cases, not perform well due to the fact that this assumes conditional independence of features and MOSTLY, this is not true for real world ...
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38 views

Which naive Bayes?

I am attempting to use a naïve Bayes classifier in python (using scikit-learn), with two examples. The first example has 6 classes and 2 hypotheses, the 2nd example has 2 classes and 6 hypotheses. ...
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29 views

Turning categorized output into continuous

I'm using a NaiveBayes algorithm that generates categorized probabilities as output instead of continuous values, which is what I need for this webapp I'm working on. Unfortunately I can't switch ...
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43 views

How to choose the right model after k-fold cross validation is done?

I'm using naive bayes to classify tweet into three classes. and i want to use k-fold cross validation to predict the right model, but i'm confused how to choose the right model after k-fold validation ...
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40 views

Independent variables in Naïve Bayes

In the perfect explanation of Bayes' Theorem here as far as I know features of the class should be independent. The question is how to prove statistically that two given features are independent? I ...
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31 views

What is the relationship between naive Bayes and Mahalanobis distance

Recently, I found a code project which uses the Mahalanobis distance to compute Bayes value, but I don't know why you can do that. Second, as I know naive Bayes is based on the Bayes rule, and how ...
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Estimating covariance for naive Bayes

I am a beginner in Pattern Recognition and started reading up Bayesian classifiers. I came across the case of naive Bayes with equal covariance in all dimensions. Given sufficient data, how does one ...
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69 views

In Kneser-Ney smoothing, how are unseen words handled?

From what I have seen, the (second-order) Kneser-Ney smoothing formula is in some way or another given as $ \begin{align} P^2_{KN}(w_n|w_{n-1}) &= \frac{\max \left\{ C\left(w_{n-1}, w_n\right) - ...
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Naive Bayes and text classification: which probability model and vectorizer combination makes sense?

I am wondering which combinations of Naive models can be paired with different vectorizing methods so that it makes sense. Let's say we have a simple binary spam-classification task. Multinomial ...
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Word probabilities in a Naive Bayes filter

While implementing a Naive Bayes filter, I stumbled across a problem with the calculation of the conditional probabilities $p(w|c)$ of a word $w \in \mathcal{W}$ given a class $c \in \mathcal{C}$. ...
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Smoothing strategies for features assuming values from countably infinite domains

I am in the midst of programming a simple Naive Bayes classifier as an exercise. It is supposed to perform word-sense disambiguation on natural language phrases, e.g. predicting the correct meaning of ...
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43 views

Parameter Estimation for Naive Bayes - Maximum a posteriori and Maximum Likelihood

I am wondering if I understand those terms correctly. To summarize my thoughts: In naive Bayes, our decision rule is basically the Maximum a posteriori (MAP) estimate of our hypothesis. We assign an ...
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35 views

Classification tips for a begginer

I'm doing a graduation work that involves applying Classification algorithms in a dataset of matches from Dota 2 (a popular MOBA game). Here's an explanation of the problem: Dota 2 matches are played ...
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29 views

Document classification problem

Assume we have $L$ labelled documents, and $U$ unlabeled ones, where all the documents from class $k$ were generated from a multinomial or Naive Bayes distribution with parameter $\theta_k$, and ...
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21 views

Entropy weighted Naive Bayes performs poorer than regular Naive Bayes?

I have a text classification problem, where there are many different classes, and the text to be classified is very short (about 1 sentence each): ...
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36 views

Naive Bayes classifier calculation

I'm trying to use naive Bayes classifier to classify my dataset.My questions are: 1- Usually when we try to calculate the likehood we use the formula: P(c|x)= P(c|x1) * P(c|x2)*...P(c|xn)*P(c) . But ...
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Post-process the output of a Multinomial Naive Bayes text classifier

I have a multinomial text classification application where there are other features than the words in text which can be useful to do the classification e.g, contains email address, contains an URL, ...
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In Naive Bayes, why bother with Laplacian smoothing when we have unknown words in the test set?

I was reading over Naive Bayes Classification today. I read, under the heading of Parameter Estimation with add 1 smoothing: "Let $c$ refer to a class (such as Positive or Negative), and let $w$ ...
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90 views

How to handle unseen features in a Naive Bayes classifier?

I am writing a naive bayes classifier for a text classification problem. I have a bunch of words and an associated label: ...
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50 views

Greater than 1 Naive Bayes Probabilities?

I am trying to train a Naive Bayes classifier. In addition to getting the most likely class as an output from the Naive Bayes classifier, I would also like to compute the probabilities associated with ...
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Variable coarsening in Naive Bayes

Say we have a binary classification problem that we solve with Naive Bayes. All features are categorical variables. Say we focus on a single feature that takes one of $N$ possible values. If $N$ is ...
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151 views

visualize the naive bayes with k-fold cv

I have done the classification using naive Bayes as a classifier, and applied 10-fold CV.I know that I can get the mean and variance of the result. However, how can I plot the classifier performance? ...
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164 views

Example of how the log-sum-exp trick works in Naive Bayes

I have read about the log-sum-exp trick in many places (e.g. here, and here) but have never seen an example of how it is applied specifically to the Naive Bayes classifier (e.g. with discrete features ...
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109 views

Gaussian Naive Bayes really equivalent to GMM with diagonal covariance matrices?

Murphy writes that a multivariate Gaussian used in a generative classifier ("Gaussian discriminant analysis"), i.e., $p(\mathbf x|y=c,\mathbf\theta) = \mathcal{N}(\mathbf x|\mathbf y_c,\mathbf ...
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386 views

Best feature selection method for naive Bayes classification

i want to make classification with naive Bayes. I have got about 100 Features. Numerical ones as well as categorical ones. Since i want only the most relevant ones to be included for the ...
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Conditional Probability With Naive Bayes

I have recently begun exploring R I have downloaded a data set that contains flight times for when a plane takes off at Origin and Lands at destination The data has up to three months’ worth of ...
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271 views

Naive Bayes: Imbalanced Dataset in Real-time Scenario

I am using scikit-learn Multinomial Naive Bayes classifier for binary text classification (classifier tells me whether the document belongs to the category X or not). I use a balanced dataset to train ...
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62 views

A Graphical Model for Fellegi-Sunter Record Linkage

I am trying to understand the Fellegi-Sunter Probability Model for Record Linkage problem. I am following the thesis at: http://www.inf.ed.ac.uk/publications/thesis/online/IM080663.pdf in order to ...
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Multinomial Naive Bayes performance with and without Bigrams/Stopwords

I have a dataset of 300 text documents that I have manually classified into three classes. The first two classes are relatively equal in size; the third class is about 40% larger than each of the ...
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How do we build a model with pyMC

I am a newbie programmer with pyMC. I have a model given as following $$\rho=\sqrt(x^2+y^2)$$ $$z=f(x,y)=\frac{c^3}{\log(c)+1}\frac{\log\rho}{\rho^2}+\frac{5.3}{r^2}\rho^{-3}$$ and I want to find the ...
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114 views

Using PyMC to obtain the posterior for the parameters of a parametric model?

I am a newbie with pyMC and I want to program an MCMC sampling for a complicated problem. I have a function given by in the following: $$g(r,c,\theta_1,\theta_2)=\frac{\delta_c}{\Sigma ...
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Are there any issues with the naive bayes classifier when the number of features are greater than the number of observations?

Say I have $f$ features and $n$ observations. If $f>>n$ are there any inherent issues that arise if a naive bayes classifier is used on such a data set? To be more concrete, let's say $f=200$ ...