The posterior distribution of the likelihood is used to interpret the evidential meaning of P-values, posterior Bayes factors and Akaike's information criterion when comparing point null hypotheses with composite alternatives. Asymptotic arguments lead to simple re-calibrations of these criteria in terms of posterior tail probabilities of the likelihood ratio. (`Prior') Bayes factors cannot be ...

Most of the Bayesian network-based classifiers are usually only able to handle discrete variables. However, most real-world domains involve continuous variables. A common practice to deal with continuous variables is to discretize them, with a subsequent loss of information. This work shows how discrete classifier induction algorithms can be adapted to the conditional Gaussian network paradigm ...

Naive Bayes is among the simplest probabilistic classifiers. It often performs surprisingly well in many real world applications, despite the strong assumption that all features are conditionally independent given the class. In the learning process of this classifier with the known structure, class probabilities and conditional probabilities are calculated using training data, and then values o...

Sentiment analysis is a challenging and interesting natural language processing task, if only because it naturally lends itself to domain adaptation. We study sentiment analysis using Naive Bayes and essentially reproducing the results from [1]. We start by describing the Naive Bayes model we use, then we describe the experimental setup and finally we discuss our observations and results. The N...

This report details the findings in building a naive Bayes sentiment classifier for a IMDB movie-review data set using Scala and ScalaNLP. We studied the unigram or bagof-words Bernoulli and Multinomial models and a number of different feature selection techniques, including term frequency, mutual information and Chi-squared. 1. DATA CORPUS The corpus contains of 2000 rated movie reviews, compr...

Due to its simplicity, efficiency, and effectiveness, multinomial naive Bayes (MNB) has been widely used for text classification. As in (NB), assumption of the conditional independence features is often violated and, therefore, reduces classification performance. Of numerous approaches alleviating features, structure extension attracted less attention from researchers. To best our knowledge, on...

Perguruan tinggi memiliki kewajiban untuk menghasilkan lulusan yang kompeten. Hal tersebut dapat dinilai dari tingkat kelulusan mahasiswanya. Selain itu, lulus tepat waktu merupakan impian para mahasiswa. Mahasiswa tidak perlu membayar biaya kuliah lagi dan bisa bekerja lebih cepat. Tetapi kondisi di lapangan, mahasiswa belum tentu menuntaskan masa studi waktu. Banyak faktor menjadi pengaruh te...