diplomsko delo
Grega Boštjančič (Avtor), Matjaž Kukar (Mentor)

Povzetek

Podatkovno rudarjenje s sistemom Oracle Data Mining (11g)

Ključne besede

Oracle;Oracle Data Miner;Weka;podatkovno rudarjenje;metode podatkovnega rudarjenja;CRISP-DM;računalništvo;visokošolski strokovni študij;diplomske naloge;

Podatki

Jezik: Slovenski jezik
Leto izida:
Tipologija: 2.11 - Diplomsko delo
Organizacija: UL FRI - Fakulteta za računalništvo in informatiko
Založnik: [G. Boštjančič]
UDK: 004.8(043.2)
COBISS: 7535188 Povezava se bo odprla v novem oknu
Št. ogledov: 76
Št. prenosov: 6
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Angleški jezik
Sekundarni naslov: [Oracle Data Mining (11g)]
Sekundarni povzetek: Data mining is becoming more and more important on number of fields in our lives. It is used by doctors defining medical conditions, bankers dealing with risk management and so on. It is a process of discovering information, patterns and correlation with searching through bigger or smaller quantity of data. Every data mining process, if one wants it to be successful, must be composed from exact steps or tasks. To reach our goal, we often have to take a step back to improve the former state. This process is standardizated with standard CRISP-DM (CRoss-Industry Standard Process for Data Mining). Data mining uses algorithms for pattern discovering as well as statistical and mathematical techniques. There are many applications which use sufisticated mix of classic and advanced algorihtms like decision tree, Naive Bayes, Support Vector Machines etc. In this paper I compared methods and scalability in two applications for data mining. The first is included in Oracle database, Oracle Data Miner, whereas the second, Weka, is independent, opensource java application. It turns out that Oracle is better with working with larger datasets while Weka is more accurate with smaller datasets. Weka's problem is mainly her wastefulness with system sources which makes her incompetent at working with large datasets. Orcale, however, sacrifaces accuracy in order to be capable of always building a model.
Sekundarne ključne besede: Oracle;Oracle Data Miner;Weka;data mining;data mining algorithem's;CRISP-DM;computer science;diploma;
Vrsta datoteke: application/pdf
Vrsta dela (COBISS): Diplomsko delo
Komentar na gradivo: Univerza v Ljubljani, Fakulteta za računalništvo in informatiko
Strani: 68 str.
ID: 24260599