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Titlebook: Credit Scoring, Response Modelling and Insurance Rating; A Practical Guide to Steven Finlay Book 2010 Palgrave Macmillan, a division of Mac

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書(shū)目名稱Credit Scoring, Response Modelling and Insurance Rating
副標(biāo)題A Practical Guide to
編輯Steven Finlay
視頻videohttp://file.papertrans.cn/240/239647/239647.mp4
圖書(shū)封面Titlebook: Credit Scoring, Response Modelling and Insurance Rating; A Practical Guide to Steven Finlay Book 2010 Palgrave Macmillan, a division of Mac
描述Every year, financial services organizations make billions of dollars worth of decisions using automated?systems. For example, who to give a credit card to and the premium someone should pay for their home insurance. This book?explains how the forecasting models, that lie at the heart of these systems, are developed and deployed.
出版日期Book 2010
關(guān)鍵詞forecasting; modeling; Parameter; Rating; Scoring; strategy
版次1
doihttps://doi.org/10.1057/9780230298989
isbn_softcover978-1-349-36689-7
isbn_ebook978-0-230-29898-9
copyrightPalgrave Macmillan, a division of Macmillan Publishers Limited 2010
The information of publication is updating

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Sample Selection,f predictor variables. Even with modern computing facilities it may not be practical to use all of the data available. There will also be cases that are not suitable for model construction, and these need to be identified and dealt with. The data used for model construction should also be as similar
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Gathering and Preparing Data,predictor variables and a dependent variable. All you had to do was read the data into the modelling software and worry about which data analysis and modelling procedures to apply. You probably didn’t have to give any thought to where the data came from or how it was prepared. In practice, it is rar
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Model Construction (Parameter Estimation),parameter estimation or modelling. Many different methods of model construction exist, and there are many theoretical arguments why one method is better than another, or why such and such a method is/is not appropriate in a given set of circumstances. However, for predictive modelling the method use
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