Title, Introduction to Data Mining with Case Studies. Author, G. K. Gupta. Publisher, Prentice-Hall Of India Pv, ISBN, , Introduction to Data Mining with Case Studies [G.K. Gupta] on * FREE* shipping on qualifying offers. Introduction to Data Mining with Case Studies [G. K. Gupta] on * FREE* shipping on qualifying offers. The field of data mining provides techniques .
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Sin-Min Lee April 4, Most case studies deal with real business problems for example, marketing, e-commerce, CRM. Try the Kindle edition and experience these great reading features: Association Rule Mining Part 2 under construction! Amazon Music Stream millions of songs. The book ensures that the students learn mininh major data mining techniques even if they do not have a strong mathematical background.
Introduction to Data Mining with Case Studies : G. K. Gupta :
Prentice-Hall of India Pvt. Instead data mining is used to uncover novel patterns in the data. Note that the quantities of items bought is ignored. The techniques include data preprocessing, association rule mining, supervised classification, cluster analysis, web data mining, search engine query mining, data warehousing and olap.
Explore the Home Gift Guide. This may involve software development for generating reports or for results visualisation and explanation for managers.
What kind of data do these cards generate? Data collection is often much better and cheaper now The need for analyzing and synthesizing information is growing in a fiercely competitive business environment of today.
A data warehouse can be of real help in data mining since data cleaning and other problems of collecting data would have already been overcome. English Choose a language for shopping. If you wish to download it, please recommend it to your friends in any social system. Amazon Renewed Refurbished products with a warranty. Registration Forgot your password? Why each of the above guidelines is important for success?
Point of sale terminals and bar codes on many products, railway bookings, educational institutions, huge number of mobile phones, electronic commerce, all generate data. Credit and debit cards. These are well structured repetitive operations easily automated. Answers to Multiple Choice Questions. A number of class projects have also been included. From its beginning in the early s, the web has grown to more than ten billion pages in estimates varyperhaps even more by the time you are looking at this slide.
Service economies are information rich and very competitive. We cannot look at all of them and so need some way to separate uninteresting results from the interesting ones. Recommendations to customers are based on past purchases and what other customers are purchasing.
INTRODUCTION TO DATA MINING WITH CASE STUDIES
The techniques introductoin data pre-processing, association rule mining, supervised classification, cluster analysis, web data mining, search engine query mining, data warehousing and OLAP. Need to serve customers better by learning from past interactions. More than million phones in India, reportedly growing at the rate of 10, new ones every hour!
The classical example is the one where a store discovered that people buying nappies tend also to buy beer.
Introduction to Data Mining with Case Studies – G.K. Gupta – Google Books
This may involve checking the accuracy and effectiveness of minning technique. Data mining is used to find the right shoes to stock in the right store.
Top Reviews Most recent Top Reviews. Only knowledge a bank has is their information stored in the computer. Why OLTP is not good for maintaining an enterprise memory? Amazon Second Chance Pass it on, trade it in, give it a second life.
Set up a giveaway. There’s a problem loading this menu right now. Every enterprise evolves with time and so must the data mining system. Look at computing trends at Question: Get to Know Us. The field is now very competitive.
Number of techniques including decision tree witj neural network. The book also provides many examples, review questions, multiple choice questions, chapter-end exercises and a good list of references and Web resources especially those which are easy to understand and useful for students.
Management view of data focuses on summary data to identify trends, challenges and opportunities. These systems have generated mountains of data. This information is used to predict the chances of a customer paying back a loan.