By George Fernandez
So much books on information mining specialise in ideas and provide few directions on how one can perform an information mining venture. info Mining utilizing SAS purposes not just introduces the major techniques but in addition allows readers to appreciate and effectively observe information mining tools utilizing robust but ordinary SAS macro-call documents. those tools pressure using visualization to completely examine the constitution of information and money the validity of statistical versions suited for data."Learn tips on how to convert laptop databases to SAS data"Discover sampling strategies to create education and validation samples"Understand frequency info research for express data"Explore supervised and unsupervised learning"Master exploratory graphical techniques"Acquire version validation suggestions in regression and classificationThe textual content furnishes thirteen easy-to-use SAS facts mining macros designed to paintings with the normal SAS modules. No extra modules or earlier adventure in SAS programming is needed. the writer exhibits the way to practice entire predictive modeling, together with facts exploration, version becoming, assumption assessments, validation, and scoring new information, on SAS datasets in under ten mins!
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Extra resources for Data Mining Using SAS Applications
Options/explanations: Possible values c:\output\ — folder named “OUTPUT” s:\george\ — folder named “George” in network drive S Be sure to include the back-slash at the end of the folder name. 6. Macro-call parameter: Display or save SAS output (required statement). Descriptions and explanation: Option for displaying all output files in the OUTPUT window or saving as a specific format in a folder specified in option #5. Options/explanations: Possible values DISPLAY: Output will be displayed in the OUTPUT window.
4. Examine the LOG window for any macro execution errors only in the DISPLAY mode. sas macro-call file, check the macro input values, and correct any input errors. 4). The PC file will be imported to a temporary (if macro input #4 is blank or WORK) or permanent (if a LIBNAME is specified in macro input option #4) SAS dataset. The output, including the first 10 observations of the imported SAS data, characteristics of numeric and character variables, simple statistics for numeric variables, and frequency information for the character variables, will be saved in the user-specified format in the userspecified folder as a single file.
Examine the contents and characteristics of the variables in the SAS data set called “fraud”. 3. 5) created by the RANSPLIT SAS macro. A box plot shows the distribution pattern and the central tendency of the data. The line between the lowest adjacent limit and the bottom of the box represents one fourth of the data. 5 A box plot illustrating the distribution pattern among the TRAINING, VALIDATION, and TEST samples for the continuous variable NETSALES generated by running the SAS macro RANSPLIT.