Database Reference
In-Depth Information
implications about the persons represented in each observation of our data set would be
unfair and misrepresentative. Thus, we will change the missing values in the current
example to illustrate how to handle missing values in RapidMiner, recognizing that what we
are about to do won't always be the right way to handle missing data. In order to have
RapidMiner handle the change from missing to 'N' for the three observations in our
Online_Gaming variable, click the design perspective icon.
Figure 3-22. Finding an operator to handle missing values.
18)
In order to find a tool in the Operators area, you can navigate through the folder tree in
the lower left hand corner. RapidMiner offers many tools, and sometimes, finding the one
you want can be tricky. There is a handy search box, indicated by the black arrow in Figure
3-22, that allows you to type in key words to find tools that might do what you need. Type
the word 'missing' into this box, and you will see that RapidMiner automatically searches
for tools with this word in their name. We want to replace missing values, and we can see
that within the Data Transformation tool area, inside a sub-area called Value Modification,
there is an operator called Replace Missing Values. Let's add this operator to our stream.
Click and hold on the operator name, and drag it up to your spline. When you point your
mouse cursor on the spline, the spline will turn slightly bold, indicating that when you let
go of your mouse button, the operator will be connected into the stream. If you let go and
the Replace Missing Values operator fails to connect into your stream, you can reconfigure
