if I can consider a variable name gender to have a level "Nominal" in the meta data creation. what kind of levels can the following have ?
Date fields - what can I set the level as?
if there are variables with single variables like "N" alone or "x" alone - What can I set the level as ?
if there are amount columns - What can I set the levels as ?
if there are blank columns - What can I set the level as ?
Hello Prajna_450 -
Here is an excerpt from the Predictive Modeling chapter (in Enterprise Miner select Help -> Contents -> Analytics -> Predictive Modeling) with some comments to help you make decisions about what measurement levels to select for the variables in your analysis.
Have a great day.
In data mining, pattern recognition, knowledge discovery, neural networks, and so on, a class variable means a categorical target variable, and classification means assigning cases to categories of a target variable. In traditional SAS procedures, class variable means simply categorical variable, either an input or a target.
The process of assigning numbers to things such that the properties of the numbers reflect some attribute of the things.
One of several ways in which properties of numbers can reflect attributes of things. The most common measurement levels are nominal, ordinal, interval, log-interval, ratio, and absolute. For details, see the Measurement Theory FAQ at ftp://ftp.sas.com/pub/neural/measurement.html.
A numeric or character categorical variable in which the categories are unordered, and the category values convey no additional information beyond category membership.
A numeric or character categorical variable in which the categories are ordered, but the category values convey no additional information beyond membership and order. In particular, the number of levels between two categories is not informative, and for numeric variables, the difference between category values is not informative. The results of an analysis that includes ordinal variables will typically be unchanged if you replace all the values of an ordinal variable by different numeric or character values as long as the order is maintained, although some algorithms might use the numeric values for initialization. SAS Enterprise Miner provides no explicit support for continuous ordinal variables, although some procedures in other SAS products do so, such as TRANSREG and PRINQUAL.
A numeric variable for which differences of values are informative.
A numeric variable for which ratios of values are informative. In SAS Enterprise Miner, ratio and higher-level variables are not generally distinguished from interval variables, since the analytical methods are the same. However, ratio measurements are required for some computations in model assessment, such as profit and ROI measures.
A variable that takes only two distinct values. A binary variable can be legitimately treated as nominal, ordinal, interval, or sometimes ratio.