1 Intelligent Data Analysis - Data Mining

Details are considered the concept of Data Mining. Described occurrence prospects, problems of data mining. A reduced look at technology
Data mining as part of the information technology market. detail ro-Looks at the concept of data. Explains the meaning of the concepts "object" and 8
"attribute", "selection", "dependent and independent variable". discuss in detail types of scales are available. Various types of data sets are given. Briefly concepts of database and DBMS. Describes the stages of data mining and actions that performed within these stages. The known classifications of methods are considered.
Data mining. The comparative characteristics of some methods, based on their properties. Characterized by the main essence of the tasks Data mining and their classification. The concepts of "information
tion, "knowledge", as well as the comparison and comparison of these concepts.

PLAN

1 Data Extraction - Data Mining.
2 Data Mining Tasks.
3 Classification of data mining tasks.
4 The task of classification and regression (the task of finding associative rules fork, clustering problem).
5 Practical application of Data Mining (Internet technology, trading
A, telecommunications, industrial production, medicine, banking business, insurance business, other applications).
6 Data Mining models (predictive models, descriptive models).
7 Data Mining methods (basic methods, fuzzy logic, genetic alte luminaries, neural networks).
8 The process of identifying knowledge (the main stages of analysis, the preparation of data).

9 Knowledge Management.
10 Data Mining Tools.
Literature: basic [1; 12; 13; 18]; additional [1; five; eight].

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Часть 1 1 Intelligent Data Analysis - Data Mining