The Naïve Bayes document classifier has been used in many document classification algorithms [1], but is only really useful on a small subset of documents due to it’s many shortcomings [2]. By augmenting the basic functionality of the simple Naïve Bayes classifier, the classification algorithm can be applied to a much wider range of documents. This paper investigates the advantages which can be...

Abstract The Threshold-based Naïve Bayes (Tb-NB) classifier is introduced as a (simple) improved version of the original classifier. Tb-NB extracts sentiment from Natural Language text corpus and allows user not only to predict how much sentence positive (negative) but also quantify with numeric value. It based on estimation single threshold value that concurs define decision rule classifies in...

in today world of internet, it is important to feedback the users based on what they demand. moreover, one of the important tasks in data mining is classification. today, there are several classification techniques in order to solve the classification problems like genetic algorithm, decision tree, bayesian and others. in this article, it is attempted to classify researchers to “expert” and “no...

cardiovascular diseases are one of the most common diseases that cause a large number of deaths each year. coronary artery disease (cad) is the most common type of these diseases worldwide and is the main reason of heart attacks. thus early diagnosis of cad is very essential and is an important field of medical studies. many methods are used to diagnose cad so far. these methods reduce cost and...

Naive Bayes is a probability-based classification method which is based on the assumption that attributes are conditionally mutually independent given the class label. Much research has been focused on improving the accuracy of Naïve Bayes via eager learning. In this paper, we propose a novel lazy learning algorithm, Selective Neighbourhood based Naïve Bayes (SNNB). SNNB computes different dist...

The problem of secure and fast distributed classification is an important one. The main focus of the paper is on privacy preserving distributed classification rule mining. This research paper addresses the performance analysis of privacy preserving Naïve Bayes classifiers for horizontal and vertical partitioned databases. The Naïve Bayes classifier is a simple but efficient baseline classifier....

In a content based image classification system, target images are sorted by feature similarities with respect to the query (CBIR). In this paper, we propose to use new approach combining distance tangent, k-means algorithm and Bayesian network for image classification. First, we use the technique of tangent distance to calculate several tangent spaces representing the same image. The objective ...

This paper introduces an algorithm that combines naïve Bayes classification with feature weighting. Most of the related approaches to feature transformation for naïve Bayes suggest various heuristics and non-exhaustive search strategies for selecting a subset of features with which naïve Bayes performs better than with the complete set of features. In contrast, the algorithm introduced in this ...