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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Adaboost step by step

So I have a table with 2 classes and binary data. D1 is the expected output and I have to perform Adaboost , to combine the classifiers in order to get the best result.(for example in row 1, BN(N3) ...
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Help Simple Conditional Counts Example

Let's say we have a sequence $S$ \begin{align} t \quad 0 \quad 1 \quad 2 \quad 3 \quad 4 \\ S_t \quad 1 \quad 1 \quad 0 \quad 0 \quad 1 \end{align} And we want to predict $S_{t+1}$ from by ...
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28 views

Large Increase in Naive Bayes Accuracy results in decrease precision?

I am trying to classify (37 possible classes) a dataset that has 9 features and 900,000 occurrences. I have tried a couple different algorithms but the one that gave the lowest logarithmic loss was ...
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66 views

Naive Bayes on a continuous dependent variable?

I read 'Design principles of massive, robust prediction systems' and have a similar requirement, i.e. a system that can evaluate new events extremely quickly (i.e. low single-digit milliseconds) and ...
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31 views

Data distribution problem

I am having the transaction dataset which contains 95% or user initiated transactions and 5% fraud transactions. When I am fitting the logistic regression model, it gives me bias prediction - as most ...
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17 views

Is it possible to achive low error on MNIST using Random Ferns?

I'm new in machine learning and i want to study how to use random ferns. I read this paper Fast Keypoint Recognition in Ten Lines of Code and implement simple version of algorithm. But then I tried ...
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14 views

Impact of conjugate priors on mutual information for Naive Bayes

I am currently thinking about the following problem. Suppose you have a simple Naive Bayes model for binary classification based on binary random variables. For example, suppose you want to predict ...
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2answers
37 views

How can I improve feature selection for my Naive Bayes Classifier?

I am classifying companies into two classes ( a particular business type, or not that business type ), using a Naive Bayes Classifier. Specifically, I'm using PHP and PHP NLP Tools. I have two ...
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21 views

Suspicious Amount of Zeros in Confusion Matrix

I have a data set with about 45000 observations and three features. When I apply machine learning classification algorithms like naive Bayes, kNN and SVM I receive a lot of zeros in the resulting ...
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28 views

Why can I use the posterior probability of a classifier as a new classifier?

I have read that, when doing discriminant analysis, you can use the posterior probability you obtain using your classifier as a new fine-tuned classifier. Can anyone talk me through the rationale of ...
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1answer
54 views

Linear discriminant analysis (Fisher) = Bayes?

I'd like to ask a question, I am reading book right now about mail filtering, both methods: naïve Bayes and Fisher are there very similar in implementation. I am also writing a paper on Bayesian spam ...
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39 views

Naive Bayes Binary Classification with Binary Features

I have a dataset with two classes $C_0$ and $C_1$. I have around $10$ to $20$ features that take binary values (either $0$ or $1$). My dataset has around $10000$ instances, with only a hundred of ...
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41 views

Can adding an additional feature to a perceptron classifier make the results worse?

I am using perceptron to solve a classification problem. I have a limited amount of features (26) and iterate through all possible combinations of them. A combination of two features [feature_a, ...
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How could these two simple Bayesian algorithms be explained, simply? [closed]

count(this token in class) + 1 / count(all tokens in class) + count( all tokens ) and ...
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1answer
23 views

Choosing smoothing parameters across multiple Naïve Bayes classifiers with different number of categories

I would like to train multiple Naïve Bayes classifiers with different number of categories, and also have a global threshold for how certain one classifier must be in order for the classification to ...
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31 views

K-cross validation and Naive Bayes

I am doing an exercise of machine learning, and I have built a Gaussian Naive Bayes classifier (i.e., I have defined values of mean and standard deviation) using scikit-learn. Now I am supposed to ...
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36 views

Is possible classify audio file using naive bayes?

I like use naive bayes classifier to classify audio file (.mp3). I use Key, Mode, Loudness, Energy and Tempo as feature. So, the classifier will classify new file to 2 class, they are POP and ROCK. ...
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10 views

Classifier with interchangeable features

I have a situation in which the features used in a classifier are multiple instances of the same kind of measurement, in random (or unknown) order; thus, a sample x1, x2, ... xn -> classA could with ...
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1answer
210 views

Buiding Ensemble model

I'm new to ensemble model. Suppose I've KNN models like this - (in R) library(class) ...
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16 views

Naive Bayes in text classification - Only classifying “0”

I have a data set of 1000 Amazon "art" category reviews. I want to classify Positive +1, Negative -1, Neutral 0 Ratings using user reviews. The final Naive Bayes classifier only predicts 0 for all ...
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1answer
44 views

How to use Naive Bayes for multi class problems?

I know how Naive Bayes work for classifying binary problems. I just need to know what are the standard way to apply NB on multi-class classification problems. Any idea please?
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246 views

How is Naive Bayes a Linear Classifier?

I've seen the other thread here but I don't think the answer satisfied the actual question. What I have continually read is that Naive Bayes is a linear classifier (ex: here) (such that it draws a ...
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31 views

Values of PDF in Bayes Classifier

I'm new here and also a beginner in statistics. I'm implementing a Bayes classifier for two classes but get confused with the value of likelihood (pdf). $$P(c|o) = p(o|c)\cdot P(c)/p(o);$$ Here ...
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55 views

Bias and variance of a naive bayes classifier and KNN classifier

After reading the paper by J. Friedman, ”On bias, variance, 0/1-loss, and the curse-of-dimensionality,” Data Mining and Knowl- edge Discovery, 1997. I would like to estimate both bias and variance ...
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25 views

Fisher's linear discriminant VS naive bayes

i know some basic things about linear classifiers. i prefer two think geometrically about them. and what'll happening if covariance Matrix were different things. Generally; What's the difference of ...
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50 views

Accuracy increases using cross-validation and decreases without

I have a question regarding cross validation: I'm using a Naive Bayes classifier to classify blog posts by author. When I validate my dataset without k-fold cross validation I get an accuracy score of ...
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29 views

sklearn - Multinomial Naive Bayes (data too big???!!!)

I wanted to really understand the rationale behind the following code as written in python sklearn's manual partial_fit(X, y, classes=None, sample_weight=None) when the data is too big to fit in ...
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1answer
34 views

From Naive Bayes to “real percentages”

I am working on a problem which is well suited to be solved with a Naive Bayes classifier: I want to know if a certain instance belongs to a certain class. I have three attributes that can help ...
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53 views

predict sales using naive bayes and handle sparse data problem

Problem I am trying to use naive bayes for ranking products in a search application. I would like to predict the sales of a given product given the search keyword and the category. the current formula ...
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30 views

Is Naive Bayes robust?

We know that according to Naive Bayes assumption input features are assumed to be independent of each others given the target variable $y$. Now, If we intentionally add a duplicate (exact copy of ...
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111 views

Naive bayes with duplicated data

In the training set for naive bayes, there are some duplicate samples. Should we train the naive bayes with duplicate samples, or should we eliminate all the duplicates and then train the naive bayes. ...
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30 views

To interpret SVM's probability output in text analysis

So, my question is about the application of the SVM's (or naive Bayes') probability output (via Platt's scaling). I know the interpretation of the output is the probability of a given observation ...
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1answer
46 views

How to deal with mixture of continuous and discrete features when using Naive Bayes classifier

My task is to use Naive Bayes classifier for prediction, where I have both continuous and discrete variables as predictor variables. In literature the classifier is written as: $$\hat{y}= ...
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105 views

Is the Naive Bayes family of classifiers linear?

There are a lot of places where you'll see the proof that Naive Bayes classifiers are linear, like this and this. But they always assume a special case of the family of Naive Bayes classifiers which ...
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34 views

Naive Bayes text classification on different cardinality classes

I have written a Naive Bayes classifier (with Laplace smoothing) and am using it to classify text into a few simple classes. However, I found that the classes are not of the same vocab size -- to be ...
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195 views

Can a Naive Bayes Model predict using pattern alone?

Say I have a set of data abc-def-ghi jkl-mno-pqr stu-vwx-yza and lots of other training samples which are catagorized as **names*. The above dataset does not have ...
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37 views

Is Laplace smoothing still good when the class sizes are unbalanced?

I'm thinking about text classification problems using naive bayes. Laplace smoothing is often recommended to eliminate zero probabilities. Let's assume that there are only two classes: A and B. ...
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Normalization of Naive Bayes output

In Scikit-learn documentation it is possible to see that the MultinomialNB estimator has a method called predict-proba in which it has the following description: "Returns the probability of the ...
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50 views

Deriving the Bayes Filter Correction Equation

The correction rule for Bayes filters is: $$p\left(x_{k}|D_{k}\right)=\dfrac{p\left(y_{k}|x_{k}\right)\cdot p\left(x_{k}|D_{k-1}\right)}{p\left(y_{k}|D_{k-1}\right)} $$ For: State at time $k$ is ...
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153 views

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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330 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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58 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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160 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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109 views

Balanced datasets in Naive Bayes

In a classification model, a desirable situation is to have classification classes evenly represented in the training dataset. Datasets that satisfy this property are called balanced datasets. ...
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1answer
46 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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2answers
131 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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90 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 ...