Database Reference
In-Depth Information
examine Figure 5-2: the yes/no attributes about whether or not a person was a member of
various types of community organizations was recorded as a 0 or 1 and those attributes
were imported as 'integer' data types. The association rule operators we'll be using in
RapidMiner require attributes to be of 'binominal' data type, so we still have some data
preparation yet to do.
Figure 5-2. Meta data of our community group involvement survey.
4)
Switch back to design perspective. We have a fairly good understanding of our objectives
and our data, but we know that some additional preparation is needed. First off, we need
to reduce the number of attributes in our data set. The elapsed time each person took to
complete the survey isn't necessarily interesting in the context of our current question,
which is whether or not there are existing connections between types of organizations in
our community, and if so, where those linkages exist. In order to reduce our data set to
only those attributes related to our question, add a Select Attributes operator to your
stream (as was demonstrated in Chapter 3), and select the following attributes for inclusion,
as illustrated in Figure 5-3: Family, Hobbies, Social_Club, Political, Professional, Religious,
Support_Group. Once you have these attributes selected, click OK to return to your main
process.
