作者:
Michael J. A. Berry
/
Gordon S. Linoff 出版社: Wiley 副标题: For Marketing, Sales, and Customer Relationship Management 出版年: 2004-4-9 页数: 643 定价: USD 50.00 装帧: Paperback ISBN: 9780471470649
Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems Each chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sale...
Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems Each chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sales, and customer support The authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data mining More advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining Covers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis
原文摘录 · · · · · ·
...build a model based on people who had ever responded to any offer in the past. Such a model would be good for discriminating between people who refuse all telemarketing calls and throw out all junk mail, and those who occasionally respond to some offers. These types of models are called nonresponse models... (查看原文)
When missing values must be replaced, the best approach is to impute them by creating a model that has the missing value as its target variable. (查看原文)
When missing values must be replaced, the best approach is to impute them by creating a model that has the missing value as its target variable. How to create such model?(7回应)
2011-11-11 11:51
When missing values must be replaced, the best approach is to impute them by creating a model that has the missing value as its target variable. 引自第74页
...build a model based on people who had ever responded to any offer in the past. Such a model would be good for discriminating between people who refuse all telemarketing calls and throw out all junk mail, and those who occasionally respond to some offers. These types of models are called nonresponse models... three blocks of input data: marketing customer info exchange details DB demographic DB
2011-11-08 11:36
...build a model based on people who had ever responded to any offer in the past. Such a model would be good for discriminating between people who refuse all telemarketing calls and throw out all junk mail, and those who occasionally respond to some offers. These types of models are called nonresponse models...引自 p35-p37
three blocks of input data:
marketing customer info
exchange details DB
demographic DB
When missing values must be replaced, the best approach is to impute them by creating a model that has the missing value as its target variable. How to create such model?(7回应)
2011-11-11 11:51
When missing values must be replaced, the best approach is to impute them by creating a model that has the missing value as its target variable. 引自第74页
...build a model based on people who had ever responded to any offer in the past. Such a model would be good for discriminating between people who refuse all telemarketing calls and throw out all junk mail, and those who occasionally respond to some offers. These types of models are called nonresponse models... three blocks of input data: marketing customer info exchange details DB demographic DB
2011-11-08 11:36
...build a model based on people who had ever responded to any offer in the past. Such a model would be good for discriminating between people who refuse all telemarketing calls and throw out all junk mail, and those who occasionally respond to some offers. These types of models are called nonresponse models...引自 p35-p37
three blocks of input data:
marketing customer info
exchange details DB
demographic DB
When missing values must be replaced, the best approach is to impute them by creating a model that has the missing value as its target variable. How to create such model?(7回应)
2011-11-11 11:51
When missing values must be replaced, the best approach is to impute them by creating a model that has the missing value as its target variable. 引自第74页
...build a model based on people who had ever responded to any offer in the past. Such a model would be good for discriminating between people who refuse all telemarketing calls and throw out all junk mail, and those who occasionally respond to some offers. These types of models are called nonresponse models... three blocks of input data: marketing customer info exchange details DB demographic DB
2011-11-08 11:36
...build a model based on people who had ever responded to any offer in the past. Such a model would be good for discriminating between people who refuse all telemarketing calls and throw out all junk mail, and those who occasionally respond to some offers. These types of models are called nonresponse models...引自 p35-p37
three blocks of input data:
marketing customer info
exchange details DB
demographic DB
0 有用 素月墨羽 2011-03-24
reading list for :Digital Technologies For Marketing
0 有用 洋葱 2013-06-05
好书
0 有用 J.X 2012-12-26
独步天下
0 有用 洋葱 2013-06-05
好书
0 有用 J.X 2012-12-26
独步天下
0 有用 素月墨羽 2011-03-24
reading list for :Digital Technologies For Marketing