This direction introduces college students to Data Mining technology, examines in element the methods, tools, and utility of Data Mining. A description of every technique is accompanied via a precise instance of its use.
The variations between Data Mining and classical statistical strategies of evaluation and OLAP structures are discussed, and the sorts of patterns published by way of Data Mining (association, classification, sequence, clustering, forecasting) are examined.
The scope of Data Mining is described. The thought of Web mining is introduced. The Data Mining strategies are regarded in detail: neural networks, choice trees, confined enumeration methods, genetic algorithms, evolutionary programming, cluster models, mixed methods. Familiarity with every technique is illustrated with the aid of fixing a sensible hassle with the assist of instrumental.
The variations between Data Mining and classical statistical strategies of evaluation and OLAP structures are discussed, and the sorts of patterns published by way of Data Mining (association, classification, sequence, clustering, forecasting) are examined.
The scope of Data Mining is described. The thought of Web mining is introduced. The Data Mining strategies are regarded in detail: neural networks, choice trees, confined enumeration methods, genetic algorithms, evolutionary programming, cluster models, mixed methods. Familiarity with every technique is illustrated with the aid of fixing a sensible hassle with the assist of instrumental.
Tools that use Data Mining technology.
The primary standards of information warehouses and the location of Data Mining in their structure are described. The standards of OLTP, OLAP, ROLAP, MOLAP, Orange software program are introduced.
The technique of information evaluation the use of Data Mining technological know-how is discussed. The ranges of this system are regarded in detail. The analyzed market of analytical software program describes merchandise from main Data Mining manufacturers, discussing their capabilities.
Purpose To acquaint college students with the theoretical elements of Data Mining technology, methods, the opportunity of their application, to provide realistic abilities in the usage of the Data Mining tools.
The primary standards of information warehouses and the location of Data Mining in their structure are described. The standards of OLTP, OLAP, ROLAP, MOLAP, Orange software program are introduced.
The technique of information evaluation the use of Data Mining technological know-how is discussed. The ranges of this system are regarded in detail. The analyzed market of analytical software program describes merchandise from main Data Mining manufacturers, discussing their capabilities.
Purpose To acquaint college students with the theoretical elements of Data Mining technology, methods, the opportunity of their application, to provide realistic abilities in the usage of the Data Mining tools.
Prior knowledge
Knowledge of pc science, the fundamentals of database theory, information of arithmetic (within the preliminary publications of a university), and facts processing science is desirable, however now not required.
Knowledge of pc science, the fundamentals of database theory, information of arithmetic (within the preliminary publications of a university), and facts processing science is desirable, however now not required.
Posts
0 Comments