-
7/24/2019 Data Preparation Techniques for Predictive Analytics
1/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
DATA PREPARATION TECHNIQUES
FOR PREDICTIVE ANALYTICS IN
SAS ENTERPRISE GUIDE
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
2/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
SAS
ENTERPRISE
GUIDE
DATA PREPARATION TECHNIQUES FOR
ANALYTICS
Data & Data Format Needed for
Predictive Modeling Create a Y or Dependent Variable
Create Model Input Variables
Replace Missing Values
Assess Normality
Transform Variables in Order to MeetAssumptions
Run Linear and Logistic Regression
Q&A
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
3/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
SCENARIO
Company sells Outdoor and Sport
Want to test a new marketing cam
Need to compile a data table with
so we can build a predictive mode
likely to respond.
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
4/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
CUSTOMER DATA
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
5/53Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
PRODUCT ORDER
DETAIL DATATRANSACTIONAL
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
6/53Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
PREDICTIVE MODEL
DEVELOPMENT
DATA
Modeling Data Set Data Warehouse
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
7/53Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
MAIN TYPES OF
DATA MARTSDATA FOR MODELING
One-Row-per-
Subject DataMart
Multiple-Row-per-Subject DataMart
LongitudinalData Mart
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
8/53Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
THE ONE-ROW-PER-
SUBJECT DATA
MART
Required by many statistical methods
Regression Analysis, Neural Networks, Decision Trees, Surviva
Cluster analysis,
Most prominent data mart structure in data mining
Event prediction (Churn, Fraud, Delinquency, Response, )
Value prediction (Purchase Size, Claim Amount, )
Segmentation (Clustering, )
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
9/53Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
OUR DESTINATION ONE ROW PER CUSTOMER
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
10/53Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
THE ONE-ROW-PER-
SUBJECT
PARADIGM
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
11/53Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
TARGET SAMPLE
Target Sample Data Warehouse
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
12/53Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
CREATE TARGET
(Y) VARIABLE
Create a variable indicating who
Purchased in the last 2 years (i.e.
January 1, 2012 December 31,
2013)
New Variable named PURCHASED1=Yes
0=No
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
13/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
DEPENDENT
VARIABLE
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
14/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
CREATE DEPENDENT (Y) VARIABLE DEMO
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
15/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
MODEL INPUTS
Data WarehouseModel Inputs
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
16/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
ENTERPRISE
GUIDEQUERY BUILDER: COMPUTED COLUMNS
COMPUTED
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
17/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
COMPUTED
COLUMNS SUMMARIZED IS ONE EXAMPLE
COMPUTED
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
18/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
COMPUTED
COLUMNS RECODED IS ANOTHER EXAMPLE
COMPUTED
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
19/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
COMPUTED
COLUMNS ADVANCED EXPRESSION IS YET ANOTHER E
C G
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
20/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
CREATE AGE
VARIABLECOMPUTED COLUMN
Calculate a customers age from their
using Advanced Expression and SAS
New Variable named AGE
YRDIF(t1.Customer_BirthDate,TODAY(),"ACT/
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
21/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
CREATE CALCULATED INPUT (AGE)
MODEL
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
22/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
O
DEVELOPMENT AND
TRANSACTION DATA
INPUT
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
23/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
POSSIBILITIES:
TABULATIONS
CREATE SUMMARY
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
24/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
CREATE SUMMARY
VARIABLESCOMPUTED COLUMNS
Calculate Summary Variables aboutpurchases
Total Amount Spent = TotalSpent
Total Number of Items Bought = TotalItems
Average Amount Spent = AvgSpent
Calculate New Variable for eachtransaction and take the Max
Longest Number of Days for a Delivery to
arrive = DaystoDeliver
CREATE SUMMARY
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
25/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
CREATE SUMMARY
VARIABLESCOMPUTED COLUMNS
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
26/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
CREATE SUMMARY INPUTS
CREATE
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
27/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
INDICATOR
VARIABLES
Calculate Indicator Variables
Did the customer buy a product in a certaline?
Childrens, Clothes & Shoes, Sports
Calculate New Variable for each transa
Product Line and summarize Total_Re
Gives us the total spent for each product Product Line Description = ProductLineD
Total of Product Line for order = OrderTot
Distinct Count of Customer_ID = Indicato
CREATE
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
28/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
CREATE
INDICATORS
CREATE CATEGORY
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
29/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
CREATE CATEGORY
TOTALS
3 TASKS TO
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
30/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
3 TASKS TO
TRANSPOSE DATA
1. Transpose Switch rows with
columns and columns with rows
2. Split Split one columns into
multiple columns
3. Stack Stack multiple columnsinto one column
SPLIT COLUMNS
THREE QUESTIONS
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
31/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
SPLIT COLUMNS
TASKTHREE QUESTIONS
1. Which column is being split?
2. Which column identifies the valu
being split?3. Which column groups the data?
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
32/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
CREATE INDICATOR INPUTSUSING RECODE, SUMMARY &
TRANSPOSE
Creating indicator variables in PROC SQL
REPLACING
http://www.nesug.org/Proceedings/nesug97/coders/eddlesto.pdfhttp://www.nesug.org/Proceedings/nesug97/coders/eddlesto.pdf -
7/24/2019 Data Preparation Techniques for Predictive Analytics
33/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
MISSING VALUES
Enterprise Guide Query Builder Compu
Replace Values
SAS Code
PROC STDIZE - documentation
SAS/STAT PROC MI - documentation
Enterprise Miner Impute Node
Class variables count, default constant valu
tree, tree surrogate
Target variables count, default constant va Interval variables mean, median, midrange
tree, tree surrogate, mid-minimum spacing, Tu
Huber, Andrews Wave, default constant
What is Missing in SAS?
REPLACEMENT TWO OPTIONSPRO
http://support.sas.com/documentation/cdl/en/statug/63347/HTML/default/viewer.htm%23statug_stdize_sect004.htmhttp://support.sas.com/documentation/cdl/en/statug/63962/HTML/default/viewer.htm%23statug_mi_sect001.htmhttp://analytics.ncsu.edu/sesug/2003/PS08-Go.pdfhttp://analytics.ncsu.edu/sesug/2003/PS08-Go.pdfhttp://support.sas.com/documentation/cdl/en/statug/63962/HTML/default/viewer.htm%23statug_mi_sect001.htmhttp://support.sas.com/documentation/cdl/en/statug/63347/HTML/default/viewer.htm%23statug_stdize_sect004.htm -
7/24/2019 Data Preparation Techniques for Predictive Analytics
34/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
REPLACEMENT TWO OPTIONS
PROC STDIZE
out =dat aprep. WhoPur chased
r eponl y mi ssi ng=0;r un;
PRO
PROC DATASETS l i b=wor k;MODI FY zer os;FORMAT _al l _;I NFORMAT _al l _;RUN;
or
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
35/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
MISSING VALUE REPLACEMENT DEMO
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
36/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
ASSESS NORMALITY
ASSESS
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
37/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
NORMALITY
Tasks
Describe
DistributionAnalysis
Graphs
Histograms
Q-Q Plot
Kernel Density Plot
ASSESS
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
38/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
NORMALITY
TasksDescribeDistribution
Analysis
4 Tests
Shapiro-Wilk
Kolmogorow-Smirnov (K-S)
Cramer-von Mises
Anderson-Darling
Testing Normality of Data using SAS
Guidos Guide to PROC Univariate: A tutorial for SAS
Users
http://www.lexjansen.com/pharmasug/2004/posters/po04.pdfhttp://www.nesug.org/Proceedings/nesug09/sa/sa07.pdfhttp://www.nesug.org/Proceedings/nesug09/sa/sa07.pdfhttp://www.nesug.org/Proceedings/nesug09/sa/sa07.pdfhttp://www.lexjansen.com/pharmasug/2004/posters/po04.pdf -
7/24/2019 Data Preparation Techniques for Predictive Analytics
39/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
ASSESS NORMALITY DEMO
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
40/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
TRANSFORM VARIABLES
TRANSFORMATIONS
FOR NORMALITY
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
41/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
FOR NORMALITY
Log
Square Root
Cube Root
Reciprocal
Square Transformation
Many more
TRANSFORMING
VARIABLES
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
42/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
VARIABLES
TotalSpent Log Transformation
Age Recode to categorical
Transforming Variables for Normality and Linearity
Before Logistic Modeling A Toolkit for Identifying an
Transforming Relevant Predictors
COMPUTED
COLUMNSADVANCED EXPRESSION
http://www.nesug.org/proceedings/nesug05/an/an7.pdfhttp://www.lexjansen.com/mwsug/2011/stats/MWSUG-2011-SA03.pdfhttp://www.lexjansen.com/mwsug/2011/stats/MWSUG-2011-SA03.pdfhttp://www.lexjansen.com/mwsug/2011/stats/MWSUG-2011-SA03.pdfhttp://www.lexjansen.com/mwsug/2011/stats/MWSUG-2011-SA03.pdfhttp://www.nesug.org/proceedings/nesug05/an/an7.pdf -
7/24/2019 Data Preparation Techniques for Predictive Analytics
43/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
COLUMNS
COMPUTED
COLUMNSRECODED
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
44/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
COLUMNS
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
45/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
TRANSFORM VARIABLES DEMO
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
46/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
RESOURCES
DATA PREPARATIONFOR ANALYTICS
-
7/24/2019 Data Preparation Techniques for Predictive Analytics
47/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
USING SAS
ISBN: 978-1-59994-047-2
SAS Bookstore Amazon
Also available for Kind
Author Page
Example Code and Data
https://support.sas.com/pubscat/bookdetails.jsp?catid=1&pc=60502https://support.sas.com/pubscat/bookdetails.jsp?catid=1&pc=60502http://www.amazon.com/Data-Preparation-Analytics-Using-Press/dp/1599940477/ref=sr_1_2?ie=UTF8&s=books&qid=1297985757&sr=8-2http://www.amazon.com/Data-Preparation-Analytics-Using-Press/dp/1599940477/ref=sr_1_2?ie=UTF8&s=books&qid=1297985757&sr=8-2http://www.amazon.com/Data-Preparation-Analytics-Using-ebook/dp/B001UQ6X2C/ref=sr_1_1?ie=UTF8&m=AG56TWVU5XWC2&s=digital-text&qid=1297985757&sr=8-1http://support.sas.com/publishing/authors/svolba.htmlhttp://support.sas.com/publishing/authors/svolba.htmlhttp://ftp.sas.com/samples/A60502http://ftp.sas.com/samples/A60502http://ftp.sas.com/samples/A60502http://support.sas.com/publishing/authors/svolba.htmlhttp://www.amazon.com/Data-Preparation-Analytics-Using-ebook/dp/B001UQ6X2C/ref=sr_1_1?ie=UTF8&m=AG56TWVU5XWC2&s=digital-text&qid=1297985757&sr=8-1http://www.amazon.com/Data-Preparation-Analytics-Using-Press/dp/1599940477/ref=sr_1_2?ie=UTF8&s=books&qid=1297985757&sr=8-2https://support.sas.com/pubscat/bookdetails.jsp?catid=1&pc=60502 -
7/24/2019 Data Preparation Techniques for Predictive Analytics
48/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
Download copy
ADDITIONAL
SUPPORTENTERPRISE GUIDE TUTORIALS
http://tdwi.org/research/2009/09/data-requirements-for-advanced-analytics.aspxhttp://tdwi.org/research/2009/09/data-requirements-for-advanced-analytics.aspx -
7/24/2019 Data Preparation Techniques for Predictive Analytics
49/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
SUPPORT
View Free Tutorials http://support.sas.com/training/resource
Getting Started with SAS Enterprise G
ADDITIONAL
RESOURCES
http://support.sas.com/training/resources/http://support.sas.com/training/resources/http://support.sas.com/documentation/onlinedoc/guide/tut43/en/menu.htmhttp://support.sas.com/documentation/onlinedoc/guide/tut43/en/menu.htmhttp://support.sas.com/documentation/onlinedoc/guide/tut43/en/menu.htmhttp://support.sas.com/training/resources/ -
7/24/2019 Data Preparation Techniques for Predictive Analytics
50/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
SOU C S
The SAS Dummy
A SAS blog for the rest of us
http://blogs.sas.com/content/sasdummy/
Chris HemedingerFollow @cjdinger
Books:
Custom Tasks for SAS Enterprise Guide U
Microsoft .NET
SAS For Dummies
AVAILABLE
PAPERS
http://blogs.sas.com/content/sasdummy/https://www.sas.com/store/prodBK_61874_en.htmlhttps://www.sas.com/store/prodBK_61874_en.htmlhttps://www.sas.com/store/prodBK_61874_en.htmlhttps://www.sas.com/store/prodBK_61874_en.htmlhttps://www.sas.com/store/prodBK_61874_en.htmlhttps://www.sas.com/store/prodBK_61874_en.htmlhttps://www.sas.com/store/prodBK_61874_en.htmlhttp://www.sas.com/store/prodBK_62824_en.htmlhttp://www.sas.com/store/prodBK_62824_en.htmlhttp://www.sas.com/store/prodBK_62824_en.htmlhttp://www.sas.com/store/prodBK_62824_en.htmlhttp://www.sas.com/store/prodBK_62824_en.htmlhttps://www.sas.com/store/prodBK_61874_en.htmlhttp://blogs.sas.com/content/sasdummy/ -
7/24/2019 Data Preparation Techniques for Predictive Analytics
51/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
Ad Hoc Data Preparation for Analysis Usin
Enterprise Guide
Introduction to Using SAS Enterprise Guid
Statistical Analysis
Introduction to Building a Linear Regressio
Take a Fresh Look at SAS Enterprise Guid
point-and-click ad hocs to robust enterprise
Advanced Analytics with Enterprise Guide
SAS Enterprise Miner Tip: Imputing Missin
FURTHER
TRAINING FROM
SAS EDUCATION
http://www.nesug.org/Proceedings/nesug09/ff/ff14.pdfhttp://www.nesug.org/Proceedings/nesug09/ff/ff14.pdfhttp://www.nesug.org/Proceedings/nesug09/ff/ff14.pdfhttp://www2.sas.com/proceedings/sugi29/117-29.pdfhttp://www2.sas.com/proceedings/sugi29/117-29.pdfhttp://www2.sas.com/proceedings/sugi29/117-29.pdfhttp://www2.sas.com/proceedings/sugi29/117-29.pdfhttp://www2.sas.com/proceedings/sugi22/STATS/PAPER267.PDFhttp://www2.sas.com/proceedings/sugi22/STATS/PAPER267.PDFhttp://www2.sas.com/proceedings/sugi22/STATS/PAPER267.PDFhttp://www.scsug.org/SCSUGProceedings/2011/schacherer2/Take%20a%20Fresh%20Look%20at%20SASR%20Enterprise%20GuideR%20-%20From%20point-and-click%20ad%20hocs%20to%20robust%20enterprise%20solutions.pdfhttp://www.scsug.org/SCSUGProceedings/2011/schacherer2/Take%20a%20Fresh%20Look%20at%20SASR%20Enterprise%20GuideR%20-%20From%20point-and-click%20ad%20hocs%20to%20robust%20enterprise%20solutions.pdfhttp://www.scsug.org/SCSUGProceedings/2011/schacherer2/Take%20a%20Fresh%20Look%20at%20SASR%20Enterprise%20GuideR%20-%20From%20point-and-click%20ad%20hocs%20to%20robust%20enterprise%20solutions.pdfhttp://www2.sas.com/proceedings/sugi28/009-28.pdfhttp://www2.sas.com/proceedings/sugi28/009-28.pdfhttp://www.youtube.com/watch?v=4VAIhWUYrWo&feature=relmfuhttp://www.youtube.com/watch?v=4VAIhWUYrWo&feature=relmfuhttp://www.youtube.com/watch?v=4VAIhWUYrWo&feature=relmfuhttp://www2.sas.com/proceedings/sugi28/009-28.pdfhttp://www.scsug.org/SCSUGProceedings/2011/schacherer2/Take%20a%20Fresh%20Look%20at%20SASR%20Enterprise%20GuideR%20-%20From%20point-and-click%20ad%20hocs%20to%20robust%20enterprise%20solutions.pdfhttp://www2.sas.com/proceedings/sugi22/STATS/PAPER267.PDFhttp://www2.sas.com/proceedings/sugi29/117-29.pdfhttp://www.nesug.org/Proceedings/nesug09/ff/ff14.pdf -
7/24/2019 Data Preparation Techniques for Predictive Analytics
52/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
SAS EDUCATION
Enterprise Guide 1 : Query and
Reporting
Enterprise Guide 2: Advanced Tasks
and Querying
Enterprise Guide for Experienced SAS
Programmers
Data Preparation for Data Mining
support.sas.com/training
https://support.sas.com/edu/schedules.html?ctry=us&id=1947https://support.sas.com/edu/schedules.html?ctry=us&id=1947https://support.sas.com/edu/schedules.html?ctry=us&id=1947https://support.sas.com/edu/schedules.html?ctry=us&id=1948https://support.sas.com/edu/schedules.html?ctry=us&id=1948https://support.sas.com/edu/schedules.html?ctry=us&id=1948https://support.sas.com/edu/schedules.html?ctry=us&id=1948https://support.sas.com/edu/schedules.html?ctry=us&id=1949https://support.sas.com/edu/schedules.html?ctry=us&id=1949https://support.sas.com/edu/schedules.html?ctry=us&id=1949https://support.sas.com/edu/schedules.html?ctry=us&id=1949https://support.sas.com/edu/schedules.html?id=74&ctry=UShttps://support.sas.com/edu/schedules.html?id=74&ctry=UShttp://support.sas.com/training/http://support.sas.com/training/https://support.sas.com/edu/schedules.html?id=74&ctry=UShttps://support.sas.com/edu/schedules.html?ctry=us&id=1949https://support.sas.com/edu/schedules.html?ctry=us&id=1948https://support.sas.com/edu/schedules.html?ctry=us&id=1947 -
7/24/2019 Data Preparation Techniques for Predictive Analytics
53/53
Copyr ight 2013, SAS Ins t i tu te Inc . A l l r i ghts reserved.
THANK YOU FOR USING SAS!