In the past few years, machine learning and in particular simple Naive Bayes classifiers have proven their value in filtering spam emails. We hereby put Naive Bayes filters to the test, against potentially more elaborate spam filters that will participate in the ceas 2008 challenge. For this purpose, we use the variants of Naive Bayes that have proven more effective in our earlier studies. Furt...

We propose the negation naive Bayes (NNB): a new method to categorize product pages on the Web depending on their information. It is a modified version of the naive Bayes (NB) and we got the idea from the complement naive Bayes (CNB). We compared the NNB with the NB and the CNB. Our experiments show that the NNB outperformed the other methods significantly when the product pages were distribute...

Data mining techniques are widely used in classification and prediction in the field of bioinformatics to analyze biomedical data. The purpose of the study is to investigate and compare (7) different classification algorithms namely, Naive Bayes, Naive Bayes updatable, FT Tree, KStar, J48, LMT, and Neural network for analyzing Hepatitis prognostic data. The results of the classification are acc...

Naive Bayes algorithm captures the assumption that every attribute is independent from the rest of the attributes, given the state of the class attribute. In this study, we attempted to increase the prediction accuracy of the simple Bayes model by integrating global and local application of Naive Bayes classifier. We performed a large-scale comparison with other attempts that have tried to impr...

Humans effortlessly use experience from related tasks to improve their performance at novel tasks. In machine learning, we are often confronted with data from "related" tasks and asked to make predictions for a new task. How can we use the related data to make the best prediction possible? In this thesis, I present the Clustered Naive Bayes classifier, a hierarchical extension of the classic Na...

Using Linux shell commands is a challenging task for most of the people new to Linux. This paper presents the idea of conversion of natural language to equivalent Linux shell command. To achieve the conversion we make use of a Naive Bayes text classifier. However there could be a case of a series of flags and combination of commands. This is handled by a sequence of Naive Bayes text classifier....

Naive-Bayes induction algorithms were previously shown to be surprisingly accurate on many classii-cation tasks even when the conditional independence assumption on which they are based is violated. However , most studies were done on small databases. We show that in some larger databases, the accuracy of Naive-Bayes does not scale up as well as decision trees. We then propose a new algorithm, ...

Naive Bayes induction algorithms were previously shown to be surprisingly accurate on many classi cation tasks even when the conditional independence assumption on which they are based is violated How ever most studies were done on small databases We show that in some larger databases the accuracy of Naive Bayes does not scale up as well as decision trees We then propose a new algorithm NBTree ...