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Kdd process

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Rajesh Chandra
Rajesh Chandra

The KDD process involves several steps: data cleaning to remove noise, data integration of multiple sources, data selection of relevant data, data transformation into appropriate forms for mining, applying data mining techniques to extract patterns, evaluating patterns for interestingness, and representing mined knowledge visually. The KDD process aims to discover useful knowledge from various data types including databases, data warehouses, transactional data, time series, sequences, streams, spatial, multimedia, graphs, engineering designs, and web data.

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KDD Process By G.Rajesh Chandra
Knowledge Discovery (KDD) Process – Data mining—core of knowledge discovery process Pattern Evaluation Data Mining Task-relevant Data Data Warehouse Data Cleaning Data Integration Databases December 26, 2013 Selection
DATA CLEANING • Remove Noise and Inconsistent Data
DATA INTEGRATION • Where multiple data sources may be combined
DATA SELECTION • Where data relevant to the analysis task are retrieved from the data base
DATA TRANSFORMATION • Where data are transformed and consolidated into forms appropriate for mining by performing summary or aggregation operation
Data Mining • An essential Process where intelligent methods are applied to extract data patterns
PATTERN EVALUATION • To identify the truly interesting patterns representing knowledge based on interestingness measures
KNOWLEDGE REPRESENTATION • Where visualization and knowledge representation techniques are used to present mined knowledge to users
WHAT KINDS OF DATA CAN BE MINED • • • • DATABASE DATA Data warehouses Transactional data Other Kinds of Data
DATABASE DATA • • • • DBMS Relational Database Examples Attributes Tuples
Data warehouses
Data Cube
Transactional Data • A Transactional data must be unique
Other Kinds of Data • • • • • • • • Time Related Data Sequence Data(Historical Records,Stock Exchange) Data streams( Video Surveillance, Sensor Data) Spatial Data(maps) Hyper Text and Multimedia Data(Text,Video,Audio) Graph and Networked Data Engineering Design Data(auto CAD) Web

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Kdd process

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