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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Any way of getting vector of probabilities for each response with Naive Bayes in R?

I'm currently using naiveBayes from {e1071}. My response is simply a prediction based on my independent variables. Is there a ...
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9 views

What is the best form (Gaussian, Multinomial) of Naive Bayes to use with (one-hot encoded) features?

I've been asked to use the Naive Bayes classifier to classify a couple of samples. My dataset had categorical features so I had to first encode them using a one-hot encoder but then I was at a loss ...
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21 views

Difference between naive Bayes / multinomial / Bernoulli / SVM

i have a question to what consider the Naive Bayes algorithms, i am confused about the difference between the 3 algorithms: 1)The original Naive Bayes, 2)Bernoulli Naïve Bayes, 3)Multinomial Naive ...
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15 views

Using the Naive Bayes classifier in R with continuous variables

I am trying to predict a categorical variable (type of job, there are three classes) using a dataset that mainly consists of continuous variables (like years of education, salary,etc), using the Naive ...
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17 views

Differences between categorical classification algorithms

Given data where the class is categorical (finite and discrete), there are multiple ways to come up with a classifier. One could use multinomial logistic regression, or support vector clustering ...
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36 views

Machine learning approach when facing low predictive power features

My dataset has 3.6k samples and 600+ one-hot encoded features. Each feature has between 5-2000 instances, averaging around 150. Intuitively, I don't believe that my features should have much ...
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1answer
27 views

The difference between the Bayes Classifier and The Naive Bayes Classifier?

I'm trying to find the connection between both classifiers. In NBC we assume that all the features are independent of each other so we can calculate the posterior probability easier. I assume Bayes ...
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67 views

Normalize non-normal distribution?

I have a query regarding a comment I found, which will surely shed some light. In this article: http://www.analyticsvidhya.com/blog/2015/09/naive-bayes-explained/ I found: If continuous features ...
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7 views

Naive Bayes and smoothing

For simplicity, let's say that we want to perform binary classification using Naive Bayes on a Boolean function. That is, the target function is $c: \{0, 1\}^n \rightarrow \{0, 1\}$. Hence, the two ...
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Is Naive Bayes suitable for large datasets with thousands of features?

I have a data set with 100 million rows and 15,000 categorical variables each with 0/1 values. My target variable is also a 0/1 binary variable. Is Naive Bayes suitable in terms of computational ...
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40 views

true negative is 0% whereas true positive is 100% correctly classified

I used Naive Bayes from Spark's MlLib to train a model and test it on the data (in the form of an RDD). The results were confusing. the data and results are as follows: The problem is a binary ...
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18 views

Simple Bayesian Classifier for spam detection

I am a very beginner at machine learning, and I'm reading a book about it. I came across some lines of code in R for naive bayesian classification for spam detection. This is the code: ...
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37 views

Naive Bayes: Intuition behind the Evidence

I understand how to use NB and have used it often. However, I am trying to understand how the two different ways I use to calculate the evidence (P(E)) result in ...
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22 views

Naive Bayes + k- fold Cross Validation

How can I find the mean and standard deviation of the accuracy of k-fold cross validation when the classifier method is Naive Bayes?
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45 views

How to compute probability

I have a dataset consisting of 4000 observation from each 324 continuous features are extracted. Each observation has been labeled a class. Since each feature from that dataset is continuous, have I ...
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31 views

how do i compute the probability [duplicate]

I have a continous dataset consisting of 4000 observation from each 400 features are extracted. Each observation has been labeled a class. Since the dataset is continous, have I created a distribution ...
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37 views

Is the dataset Normally distributed?

So based from this link http://www.simafore.com/blog/bid/107702/2-ways-of-using-Naive-Bayes-classification-for-numeric-attributes I began to realize it might be a good idea to compute the pdf of ...
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12 views

Would it make sense to train a naive bayes model with PCA compressed data?

I would like to improve my result from my training, from which i was thinking maybe PCA could be able to help determine which features are useful for my classification task. But would that help?
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Create a model based on the distribution of data for classification purposes

I have data set which is stored as a matrix where each row is an observation (number of observations listed is 4000 ) and each column the feature extracted from that observation (number of features ...
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23 views

why am i getting bad predictions rates?

I am trying to make a classifier capable of recognizing digits using the naive bayes method. Problem is though that i am getting pretty bad results. I thought the reason would be because of the ...
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19 views

How to interpret the the train result?

I using the caret trained my dataset using naive bayesian as method with an repeated 10-fold cross validation. I seem to get a lot of different output, but can't ...
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13 views

How should i represent my data for a naive bayesian based classifier?

I am at the moment trying to find out how well the naive bayesian method works for classification purposes. The data I am having is hand written characters ("A", "B","C", "D"). My dataset is stored ...
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1answer
60 views

How was this intergral derived from Bayes' Rule in David Heckerman's Bayesian Network paper?

I am trying to follow this paper titled "A Tutorial on Learning With Bayesian Networks" by Microsoft researcher David Heckerman. In it I am unable to figure out how he got to Equation 2 from ...
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15 views

Weka Experimenter Tool (xx/yy/zz) explanation

I am using Weka experimenter tool and I need help to fully understand how this count works. I found this explanation in a paper: The annotation v or * indicates that a specific result is ...
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25 views

What is the meaning of laplace, eps and threshold in NaiveBayes package in R e1071 lib?

I am using NaiveBayes for text classification, I am interested on tagging a text (like a blog post). What I am finding is that normally I have results in which a tag has a probability of 0.9999 of ...
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34 views

How to extract the predictions and probabilities of each training sample in a cross-validation result in caret (R)?

I'm learning the caret package in R for classifications by Naive Bayes. I'm following the tutorial from: http://topepo.github.io/caret/training.html Thanks for the great tutorial! But I have one ...
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34 views

Does Naive Bayes( library:klar) in R calculates denominator of conditional probability while giving output?

Generally, when using Naive Bayes for classification, denominator is ignored as probability is directly proportional to the numerator as denominator is same for all the classes. So, I want to know if ...
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13 views

pairwise chi square test for independence on large df

I have a data frame (mydata) of discrete data (binned 1 through 10) where each column represents a variable I'd like to use in a Naive Bayes algorithm and each row represents a city throughout Europe. ...
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18 views

What algorithm would you use for this problem?

I want to compare two sets of data to predict if someone is going to get sick or not. (both datasets are from the same subject) Dataset 1 :The training set is a matrix (7 col x 14 rows) of daily ...
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1answer
38 views

Choosing number of samples to train a model

(On behalf of a colleague) I have performed some modelling based on a naïve Bayes classifiers model (weighted genomic risk score) and obtained reasonable ROCAUC results (used ROCR, pROC, and SDMtools ...
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2answers
107 views

“Good” classifier destroyed my Precision-Recall curve. What happened?

I'm working with imbalanced data, where there are about 40 class=0 cases for every class=1. I can reasonably discriminate between the classes using individual features, and training a naive Bayes and ...
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11 views

Help me inform multiple regression coefficients with additional dataset

I have a data set with 24 year on year observations. That is for a single company. I have around 500 companies with incomplete datasets (i.e. with missing values). I am trying to predict a Y ...
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26 views

Any additional suggestion to combine weights and probabilities in Naive Bayes to classify tweets

As a side project, I am trying to build a simple Naïve Bayes sentiment analysis model to classify the sentiment of some tweets as either positive or negative. But I am trying to incorporate sentiment ...
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34 views

Hypothesis space of Naive Bayes and kNN

I am confused about the hypothesis space of those two classifiers. In the case of linear regression, it's pretty straightforward ; the possible hypothesis are equations of lines, that is, linear ...
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75 views

Highly correlated features in text mining despite mutual information criterion

I'm trying to classify documents into two classes using the Bernoulli Naive Bayes algorithm, as described here in chapter 13. I've extracted 500 tokens (out of more than 30,000) from my sample ...
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23 views

Intuitive example for MLE, MAP and Naive Bayes classifier

I am trying to understand MLE, MAP and naive Bayes classifier, but it's difficult to understand the differences without some numerical example. Can someone give simple intuitive numerical example for ...
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2answers
41 views

Text categorization using Naive Bayes: Why isn't this working?

I'm trying to implement a system for text categorization using Naive Bayes as part of a school project. I have to hand code the algorithm and have been having some issues. To make sure I understand ...
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75 views

Algebraic classifiers, more information?

I have read Algebraic classifiers: a generic approach to fast cross-validation, online training, and parallel training and was amazed by the performance of the derived algorithms. However, it seems ...
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60 views

Why does Naive Bayes use gaussian pf rather than Student's t?

Every source in the literature I could find about naive Bayes mentions using a gaussian's probability density function, using the mean and variance estimated from the data itself. This strikes me as ...
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1answer
57 views

Very poor accuracy in Naive Bayes for ancestry/surname classification

Naive Bayes has a very good reputation on the classification of surnames by ancestry (see http://www.ncbi.nlm.nih.gov/pubmed/24944286). I would like to apply a Naive Bayes classifier in R to ...
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34 views

How to apply a fitted Tree-augmented Naive Bayes classifier to new cases

I am running Tree Augmented Naive Bayes algorithm in R and I have got the desired network. However, unlike logistic regression, Bayesian is non-parametric i.e. I do not have any coefficients which I ...
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11 views

Naive Bayes Bernoulli with more than 2 class labels?

I am a little confused about how to perform Naive Bayes Bernoulli model. In the first link, they split the class labels and the predictors. It is a binary class label here. But what if I do not have a ...
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61 views

Creating Naive Bayes Model for numerical data in R

I want to calculate the missing value using the NaiveBayes predictor. I am using a dataset with missing values at some rows, ...
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37 views

What is the Bernoulli class conditional distribution?

What is the Bernoulli class conditional distribution? I am trying to implement a procedure for computing a naive Bayes classifier for binary features with a Bernoulli class conditional distribution. ...
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27 views

How do I reduce number of features without rebuilding the model?

I'm pretty new to ML/NLP thus my question maybe naive. How do I reduce number of features without rebuilding the model for Naive Bayes Classification? I'm using MALLET to build the model to classify ...
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62 views

Classifying time-series similarity - what variable should I train on?

I have ~10,000 time series, each with 65 time points. I'm interested in classifying each pair of time series as "similar" or "not similar". Here's an example of two similar (left) and not similar time ...
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1answer
128 views

Naive Bayes error with caret

I want to predict a variable with Naive Bayes. I tried it with another one from the same dataset and it worked perfect but not with the desired. The variable to predict contains values like "OL","DL" ...
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60 views

SVM classifier - can I average multiple models?

I'm performing SVM classification on a relatively large data set (~1M rows, 4 variables). I want to assign a classification score to each row, not evaluate input parameters, so following the top ...
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Is the Laplace/Lidstone smoothing parameter (talking about Multinomial/Bernoulli Naive Bayes) related to the particular structure of the dataset?

I'm working with Multinomial and Bernoulli Naive Bayes implementation of scikit-learn (python) for text classification. I'm using the 20_newsgroups dataset. From the scikit documentation we have: ...
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Naive bayes - parameters count

How many parameters do we have to estimate using naive bayes when the input features are conditionaly Independent and when they are not? Is there a formula that can fit - boolean, discrete and ...