This is an undergraduate introduction to data mining. The book doesn't go into details. It may be suitable for people who want to get a quick feel of the data mining field. People who need more details shall read more serious and comprehensive introductions. Overall I am giving 4 stars, because I li
Principles of data mining
โ Scribed by M A Bramer
- Publisher
- Springer
- Year
- 2007
- Tongue
- English
- Leaves
- 353
- Series
- Undergraduate topics in computer science
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Given the clinical success and worldwide publicity for erectile dysfunction treatment and then the adverse cardiac reactions, mostly heart failure, in some patients, clinicians began to worry about the safety of the new drugs currently available to the public. Graham Jackson, a well-known expert and lecturer on cardiac problems and erectile dysfunction, provides the reader with straightforward guidelines on the pharmacological, social and sexual benefits of correct dosing in various types of patient groups "Data mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas." "This book explains and explores the principal techniques of Data Mining for classification, generation of association rules and clustering. It is written for readers without a strong background in mathematics or statistics and focuses on detailed examples & explanations of the algorithms given."--Jacket. Read more...
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This book explains the principal techniques of data mining: for classification, generation of association rules and clustering. It is written for readers without a strong background in mathematics or statistics and focuses on detailed examples and explanations of the algorithms given. This will bene
This book explains the principal techniques of data mining: for classification, generation of association rules and clustering. It is written for readers without a strong background in mathematics or statistics and focuses on detailed examples and explanations of the algorithms given. This will bene
This book explains the principal techniques of data mining: for classification, generation of association rules and clustering. It is written for readers without a strong background in mathematics or statistics and focuses on detailed examples and explanations of the algorithms given. This will bene
This book explains the principal techniques of data mining: for classification, generation of association rules and clustering. It is written for readers without a strong background in mathematics or statistics and focuses on detailed examples and explanations of the algorithms given. This will bene