SubjectsSubjects(version: 928)
Course, academic year 2022/2023
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Internet and Classification Methods - NAIX105
Title: Internet a klasifikační metody
Guaranteed by: Student Affairs Department (32-STUD)
Faculty: Faculty of Mathematics and Physics
Actual: from 2022
Semester: summer
E-Credits: 3
Hours per week, examination: summer s.:1/1, C+Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
Virtual mobility / capacity: no
State of the course: taught
Language: Czech
Teaching methods: full-time
Is provided by: NAIL105
Guarantor: prof. RNDr. Ing. Martin Holeňa, CSc.
Class: Informatika Mgr. - volitelný
Classification: Informatics > Informatics, Software Applications, Computer Graphics and Geometry, Database Systems, Didactics of Informatics, Discrete Mathematics, External Subjects, General Subjects, Computer and Formal Linguistics, Optimalization, Programming, Software Engineering, Theoretical Computer Science
Pre-requisite : {NXXX038, NXXX039, NXXX040, NXXX067, NXXX069}
Incompatibility : NAIL105
Interchangeability : NAIL105
Annotation -
Last update: T_KTI (29.03.2013)
Attending the course, the students get acquainted with classification methods used in three important internet or general-network applications: spam filtering, recommender systems, and intrusion detection systems. However, they learn more than only how classification is performed when facing these three problems. On the background of the above applications, they get an overall overview about the fundamentals of classification methods. The course is taught in a 2-week cycle, always a 2h lecture and a 2h practice at computer labs.
Aim of the course -
Last update: prof. RNDr. Ing. Martin Holeňa, CSc. (29.06.2019)

Give to the students an overview of the spectrum of classification methods used ore usable in internet applications.

Course completion requirements -
Last update: prof. RNDr. Ing. Martin Holeňa, CSc. (29.06.2019)

The course is credited for participation at seminars and writing a project essay, and for a subsequent exam. The credits for seminars and essay have to be obtained before the exam.

Literature -
Last update: T_KTI (09.05.2014)

E. Blanzieri, A. Bryl. A survey of learning-based techniques of email spam filtering. Artificial Intelligence Reiviews, 29 (2006) 63-92.

D.J. Hand. Construction and Assessment of Classification Rules. Wiley, 1997.

L.I. Kuncheva. Combining Pattern Classifiers: Methods and Algorithms. Wiley, 2004.

A. Shabtai, R. Moskowitch, Y. Elovici, C. Glezer. Detection of malicious code by applying machine learning classifiers on static features: A state-of-the-art survey. Information Security, 14 (2009) 16-29.

Requirements to the exam - Czech
Last update: prof. RNDr. Ing. Martin Holeňa, CSc. (13.10.2017)

Ústní zkouška, při které si student losuje jedno z témat probíraných při 2.-6. přednášce.

Syllabus -
Last update: T_KTI (09.05.2014)

Three important internet applications of classification methods: spam filtering, recommender systems, intrusion detection systems.

Basic concepts concerning classification.

Main kinds of classification methods.

When does a classifier make the least errors on new data?

When is classification comprehensible for a user?

Combining a number of classifiers into a team.

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