By SAS Institute
Information mining helps you to observe beneficial hidden info on your information and use it to resolve your online business difficulties. This introductory advisor to facts mining makes use of a case learn procedure that takes you thru the SAS company Miner interface from preliminary info entry to numerous accomplished analyses, similar to predictive modeling, clustering research, organization research, and hyperlink research. while you're a brand new SAS company Miner person, you will discover this pleasant consultant to be a useful source as you navigate the interface. After finishing the case reviews during this advisor, you'll be ready to take on the extra complex statistical analyses which are lined within the SAS company Miner on-line reference documentation.
Read or Download Data Mining Using SAS Enterprise Miner - A Case Study Approach PDF
Similar mathematical & statistical books
Explains the best way to elevate the modularity, flexibility, and maintainability of your SAS code utilizing the SAS macro facility. presents entire information regarding macro language parts, interfaces among the SAS macro facility and different elements of SAS software program, and macro processing regularly.
You could research loads of arithmetic during this booklet yet not anything approximately MATLAB. there's no sturdy perform during this ebook. a touch for the writer. try and make a CD-ROM with all examples on it. So every person can get acquainted with MATLAB and the outside. most sensible will be to double or triple the variety of examples. (good examples in MATLAB Code) reconsider it and that i could be the first who buys the enhanced variation of this publication or you simply need to swap the identify in :Advanced Engineering arithmetic photos via MATLAB.
A brand new version of this best-selling introductory ebook to hide the most recent SPSS types eight. zero - 10. zero This e-book is designed to educate novices how you can use SPSS for home windows, the main standard computing device package deal for analysing quantitative facts. Written in a transparent, readable and non-technical type the writer explains the fundamentals of SPSS together with the enter of information, information manipulation, descriptive analyses and inferential suggestions, together with; - developing utilizing and merging info documents - developing and printing graphs and charts - parametric exams together with t-tests, ANOVA, GLM - correlation, regression and issue research - non parametric checks and chi sq. reliability - acquiring neat print outs and tables - incorporates a CD-Rom containing instance information documents, syntax documents, output documents and Excel spreadsheets.
The SPSS sixteen. zero short advisor offers a suite of tutorials to acquaint you with the elements of the SPSS procedure. issues comprise examining information, utilizing the knowledge Editor, analyzing precis facts for person variables, operating with output, developing and modifying charts, operating with syntax, enhancing facts values, sorting and choosing information, and acting extra statistical systems.
- Mathematical Statistics and Limit Theorems: Festschrift in Honour of Paul Deheuvels
- Essential Statistical Inference: Theory and Methods
- Statistics Using SAS Enterprise Guide
- Common Statistical Methods for Clinical Research with SAS Examples, Second Edition
- Microeconometrics Using Stata
- Reading External Data Files Using SAS: Examples Handbook
Extra info for Data Mining Using SAS Enterprise Miner - A Case Study Approach
Create a new variable INDEROG that indicates whether DEROG is greater than 0. Repeat the process for DELINQ but name the new variable INDELINQ. To create the variable INDEROG: 1 Select Tools Create Variable from the main menu. Alternately, you can click the Create Variable ( icon in the toolbox). ) tool 2 Type INDEROG in the Name box. 3 Select Define. 4 Type in the formula DEROG > 0. This definition is an example of Boolean logic and illustrates a way to dichotomize an interval variable. The statement is either true or false for each observation.
In the Model Manager, select Tools Lift Chart A cumulative %Response chart appears. By default, this chart arranges observations (individuals) into deciles based on their predicted probability of response, and then plots the actual percentage of respondents. For this example, the individuals are sorted in descending order of their predicted probability of default on a loan. The plotted values are the cumulative actual probabilities of loan defaults. If the model is useful, the proportion of individuals that defaulted on a loan will be relatively high in the top deciles and the plotted curve will be decreasing.
1. If necessary, change the measurement level for DEROG and DELINQ to ordinal. This is not done in this example. To modify the measurement level information for DEROG, proceed as follows: 1 Right-click the Measurement Level column of the row for DEROG. 2 Select Set Measurement Level ordinal 3 Repeat steps 1 and 2 for DELINQ. Alternatively, you could have updated the model role information for both variables simultaneously by selecting the rows for both DEROG and DELINQ before following steps 1 and 2.