Download PDF by S. Prabhu, N. Venatesan: Data mining and warehousing

By S. Prabhu, N. Venatesan

ISBN-10: 8122419720

ISBN-13: 9788122419726

ISBN-10: 8122424325

ISBN-13: 9788122424324

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55) (d) Operator Manipulation: This method involves changing the operators randomly in an operator tree and hence is used with tree-encoded problems. * x + x y 3 + y 3 Fig. 10 Operator manipulation Here we observe that the divide operator in the parent is randomly changed to the multiplication operator. 1 What is Clustering? Clustering can be considered the most important unsupervised learning problem; so, as every other problem of this kind, deals with finding a structure in a collection of unlabeled data.

The process of inspecting data for physical inconsistencies, such as orphan records or required fields set to null, and logical inconsistencies, such as accounts with closing dates earlier than starting dates. Data cleaning is separate from data enrichment and data transformation because data cleaning attempts to correct misused or incorrect attributes in existing data. Data enrichment, by contrast, adds new attributes to existing data, while data transformation changes the form or structure of attributes in existing data to meet specific data mining requirements.

Examples of classification methods used as part of knowledge discovery applications include classifying trends in financial markets and automated identification of objects of interest in large image databases. Prediction involves using some variables or fields in the database to predict unknown or future values of other variables of interest. Description focuses on finding human interpretable patterns describing the data. 3 NEURAL NETWORKS Neural Networks are analytic techniques modeled after the (hypothesized) processes of learning in the cognitive system and the neurological functions of the brain and capable of predicting new NEURONS INPUT LAYER 1 LAYER 2 Fig.

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Data mining and warehousing by S. Prabhu, N. Venatesan

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