By George Fernandez (auth.)

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**Extra resources for Data Mining Using SAS Applications, 1st Edition**

**Sample text**

Bles used in modeling is an important data mining requirement. The variables can be generally classified into continuous or categorical. Preparing Data for Data Mining • 17 Continuous variables are numeric variables that describe quantitative attributes of the cases and have a continuous scale of measurement. Means and standard deviations are commonly used to quantify the central tendency and dispersion. Total sales per customers and total manufacturing costs per products are examples of interval scales.

The variables can be generally classified into continuous or categorical. Preparing Data for Data Mining • 17 Continuous variables are numeric variables that describe quantitative attributes of the cases and have a continuous scale of measurement. Means and standard deviations are commonly used to quantify the central tendency and dispersion. Total sales per customers and total manufacturing costs per products are examples of interval scales. An interval-scale target variable is a requirement for multiple regression and neural net modeling.

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. One fourth of the data fall between the bottom of the 1. 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. box and the median, and another one fourth between the median and the top of the box.