BookmarkSubscribeRSS Feed
beckeybianc
Calcite | Level 5

Hi everybody,

 

I like SAS EM but i stucked.

Can you explain me datasource variable roles? When should i use them? And what is Drop, Report and Level?

 

Assessmet

Censor

Classification

Cost

Cross ID

Decision

Frequency

ID

Input

Key

Label

Prediction

Referrer

Residual

Segment

Sequence

Target

Text

Text Location

Time ID

Treatment

Web Address

 

best regards

 

1 REPLY 1
WendyCzika
SAS Employee

In the SAS EM Reference Help (from Help>Contents in EM), go to Data Sources>SAS Enterprise Miner Sources, then the section "Model Roles and Measurement Levels of Variables" and it has the information on all of these variable roles.  Drop, Report, and Level are explained in there too, but I'll include that here since that part isn't too big 🙂

 

• Level — is the measurement level of the variable. (MORE BELOW)
• Report — indicates whether a variable should be automatically included in reports such as the predictive model assessment decile and percentile tables.
• Drop — drops the variable.

Select one of the following measurement levels:
• Binary — contains two discrete values (for example, PURCHASE: Yes, No).
• Interval — contains values that vary across a continuous range (for example, TEMP: 0, 32, 34, 36, 50, 56, 80, ...., 102).
• Nominal — contains a discrete set of values that do not have a logical ordering (for example, PARTY: Democrat, Republican, other).
• Ordinal — contains a discrete set of values that do have a logical ordering (for example, GRADE: A, B, C, D, F).
• Unary — contains one discrete value.

sas-innovate-2024.png

Don't miss out on SAS Innovate - Register now for the FREE Livestream!

Can't make it to Vegas? No problem! Watch our general sessions LIVE or on-demand starting April 17th. Hear from SAS execs, best-selling author Adam Grant, Hot Ones host Sean Evans, top tech journalist Kara Swisher, AI expert Cassie Kozyrkov, and the mind-blowing dance crew iLuminate! Plus, get access to over 20 breakout sessions.

 

Register now!

How to choose a machine learning algorithm

Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 1 reply
  • 738 views
  • 0 likes
  • 2 in conversation