Input - Aster Analytics

Teradata Aster Analytics Foundation User Guide

Product
Aster Analytics
Release Number
6.21
Published
November 2016
Language
English (United States)
Last Update
2018-04-14
dita:mapPath
kiu1466024880662.ditamap
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AA-notempfilter_pdf_output.ditaval
dita:id
B700-1021
lifecycle
previous
Product Category
Software

The input table, housing_train, is real estate data on homes, which models the home price with 12 predictors (six numerical and six categorical variables). The variable definition is:

Response Variable Predictor Description
price   Sale price of a house in $
  lotsize Lot size of property in square feet
  bedrooms Number of bedrooms in house
  bathrms Number of full bathrooms in house
  stories Number of stories in house, excluding basement
  driveway Whether the property has a driveway
  recroom Whether the house has a recreation room
  fullbase Whether the house has a full, finished basement
  gashw Whether the house uses gas to heat water
  airco Whether the house has central air conditioning
  garagepl Number of places in the garage
  prefarea Whether the house is located in a preferred neighborhood of the city
  homestyle Architectural style of the house
GLM Example 3 Input Table housing_train (Columns 1-7)
sn price lotsize bedrooms bathrms stories driveway
1 42000 5850 3 1 2 yes
2 38500 4000 2 1 1 yes
3 49500 3060 3 1 1 yes
4 60500 6650 3 1 2 yes
5 61000 6360 2 1 1 yes
6 66000 4160 3 1 1 yes
7 66000 3880 3 2 2 yes
8 69000 4160 3 1 3 yes
9 83800 4800 3 1 1 yes
10 88500 5500 3 2 4 yes
... ... ... ... ... ... ...
GLM Example 3 Input Table housing_train (Columns 8-14)
recroom fullbase gashw airco garagepl prefarea homestyle
no yes no no 1 no Classic
no no no no 0 no Classic
no no no no 0 no Classic
yes no no no 0 no Eclectic
no no no no 0 no Eclectic
yes yes no yes 0 no Eclectic
no yes no no 2 no Eclectic
no no no no 0 no Eclectic
yes yes no no 0 no Eclectic
yes no no yes 1 no Eclectic
... ... ... ... ... ... ...