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Intelligent Systems Lecture 23 Introduction to Intelligent Data Analysis (IDA). Example of system for Data Analyzing based on neural networks

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Synonyms of IDA Data mining Knowledge discovery, in particular, Knowledge Discovery in Databases (KDD) Knowledge acquisition

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Data Mining: Definition Data Mining is a collection of technologies which employ modern analysis techniques and computer power to find structure in data. Data Mining is composed of several branches, each of which attempts to solve a different problem.

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Place of KDD in Decision support system (in medicine)

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Place of Data Mining in Knowledge Discovery (Jiavei Han, Micheline Kamber “Data Mining. Concepts and techniques”)

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Data Mining: Ontology Predictive Modeling Clustering Deviation Detection Text Mining Link Analysis Etc....

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Data Mining: Modeling Predictive Modeling attempts to predict values of future cases based on historical examples 90+% of all data mining is modeling Two major types: –estimation –classification Related to statistical regression

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Data Mining: Clustering Clustering attempts to separate cases into ‘natural’ groupings. Strictly, there are no ‘right answers’ Tends to be compute intensive Very popular in marketing, as market segmentation

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Data Mining: Deviation Detection Deviation detection identifies cases which are ‘unexpected’ All algorithms assume some model of ‘normality’- what is expected Related to outlier detection in conventional statistics

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Data Mining: Text Mining Text mining includes several, different methods for discovering structure in documents. The most common text mining applications are search and retrieval tools.

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Data Mining: Link Analysis Link analysis searches for indirect connections between items Primarily employed in fraud detection and law enforcement Link analysis tools typically include a data visualization component

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Structure of software AnalDB Shell DLL … Modules with NNs Database User BDE GUI, generation of reports Control of NN Reading from Database, Options, Commands

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