Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: Naive Bayes

Sortuj według:

Ogranicz wyniki do:

Predicting word order universals

Merlo P.

Journal of Language Modelling

2015

Vol. 3, No. 2

317--344

This paper shows a computational learning paradigm to compare and test theories about language universals. Its main contribution lies in the illustration of the encoding and comparison of theories about typological universals to measure the generalisation ability of these theories. In so doing, this method uncovers hidden dependencies between theoretical dimensions and primitives that were considered independent and independently motivated.

Comparative Study of Supervised Learning Methods for Malware Analysis

Kruczkowski M., Niewiadomska-Szynkiewicz E.

Journal of Telecommunications and Information Technology

2014

nr 4

24--33

Malware is a software designed to disrupt or even damage computer system or do other unwanted actions. Nowadays, malware is a common threat of the World Wide Web. Anti-malware protection and intrusion detection can be significantly supported by a comprehensive and extensive analysis of data on the Web. The aim of such analysis is a classification of the collected data into two sets, i.e., normal and malicious data. In this paper the authors investigate the use of three supervised learning methods for data mining to support the malware detection. The results of applications of Support Vector Machine, Naive Bayes and k-Nearest Neighbors techniques to classification of the data taken from devices located in many units, organizations and monitoring systems serviced by CERT Poland are described. The performance of all methods is compared and discussed. The results of performed experiments show that the supervised learning algorithms method can be successfully used to computer data analysis, and can support computer emergency response teams in threats detection.