Based on the analysis and distribution of network attacks in KDDCup99 dataset and real time traffic, this paper proposes a design of multi stage filter which is an efficient and effective approach in dealing with various categories of attacks in networks. The first stage of the filter is designed using Enhanced Adaboost with Decision tree algorithm to detect the frequent attacks occurs in the n...

The tembang macapat can be classified using its cultural concepts of guru lagu, wilangan, and gatra. People may face difficulties recognizing certain songs based on the established rules. This study aims to build classification models a simple yet powerful Naïve Bayes classifier. Naive generate high-accuracy values from sparse data. modifies concept Guru Lagu by retrieving last vowel each line....

Abstrak - Tingginya kecenderugan masyarakat dalam mengakses berita secara online, membuat editor dan portal harus menyediakan yang berkualitas. Namun pada tersebut masih diklasifikasikan umum, sehingga ketika pembaca ingin mendapatkan kategori lebih spesifik dilakukan manual dengan menyaring berita-berita tersebut. Hal ini juga dialami oleh bidang sosial Badan Pusat Statistik Provinsi Riau kesu...

Due to huge amount of increase in text data, its classification has become an important issue, now days. There are many good classification techniques discussed in this paper. Each classification method has its own assumptions, advantages and limitations. One of the most widely used classifier is Naïve Bayes which performs well with different data sets. Various Smoothing techniques are applied ...

In this paper, we propose a novel feature selection method— INTERACT to select relevant words of emails for spam email filtering, i.e. classifying an email as spam or legitimate. Four traditional feature selection methods in text categorization domain, Information Gain, Gain Ratio, Chi Squared, and ReliefF, are also used for performance comparison. Three classifiers, Support Vector Machine (SVM...

As the number of web logs dramatically grows, readers are turning to them as an important source of information. Automatic techniques that identify the political sentiment of web log posts will help bloggers categorize and filter this exploding information source. In this paper we illustrate the effectiveness of supervised learning for sentiment classification on web log posts. We show that a N...

In this study, we present a new classifier that combines the distance-based algorithm K-Nearest Neighbor and statistical based Naïve Bayes Classifier. That is equipped with the power of both but avoid their weakness. The performance of the proposed algorithm in terms of accuracy is experimented on some standard datasets from the machine-learning repository of University of California and compar...

Data uncertainty is widespread in real-word applications. It has captured a lot of attention, but little job has been paid to the research of cost sensitive algorithm on uncertain data. The paper proposes a novel cost-sensitive Naïve Bayes algorithm CS-DTU for classifying and predicting uncertain datasets. In the paper, we apply probability and statistics theory on uncertain data model, define ...