To use
the StatExplore node to produce a statistical summary of the input data, complete
the following steps:
-
Select
the
Explore tab on the Toolbar.
-
Select
the StatExplore node icon. Drag the node into the Diagram Workspace.
Tip
To determine
which node an icon represents, position the mouse pointer over the
icon and read the tooltip.
-
Connect
the DONOR_RAW_DATA input data source node to the StatExplore node.
To connect
the two nodes, position the mouse pointer over the right edge of the
input data source node until the pointer becomes a pencil. With the
left mouse button held down, drag the pencil to the left edge of the
StatExplore node. Then, release the mouse button. An arrow between
the two nodes indicates a successful connection.
-
Select
the StatExplore node. In the Properties Panel, scroll down to view
the Chi-Square Statistics properties. Click on the value of
Interval Variables and select
Yes from the drop-down menu that appears.
Chi-square
statistics are always computed for categorical variables. Changing
the selection for interval variables causes SAS Enterprise Miner to
distribute interval variables into five (by default) bins and compute
chi-square statistics for the binned variables when you run the node.
-
In the
Diagram Workspace, right-click the StatExplore node, and select
Run from the resulting menu. Click
Yes in the confirmation window that opens.
When you
run a node, all of the nodes preceding it in the process flow are
also run in order, beginning with the first node that has changed
since the flow was last run. If no nodes other than the one that you
select have changed since the last run, then only the node that you
select is run. You can watch the icons in the process flow diagram
to monitor the status of execution.
-
Nodes that are outlined in green
are currently running.
-
Nodes that are denoted with a check
mark inside a green circle have successfully run.
-
Nodes that are outlined in red
have failed to run due to errors.
In this
example, the DONOR_RAW_DATA input data node had not yet been run.
Therefore, both nodes are run when you select to run the StatExplore
node.
-
In the
window that appears when processing completes, click
Results. The Results window opens.
Note: Panels in Results
windows might not have the same arrangement on your screen, due to
window resizing. When the Results window is resized, SAS Enterprise
Miner redistributes panels for optimal viewing.
The results
window displays the following:
-
a plot that orders the variables
by their worth in predicting the target variable.
Note: In the StatExplore
node, SAS Enterprise Miner calculates variable worth using the Gini
split worth statistic that would be generated by building a decision
tree of depth 1. For detailed information about Gini split worth,
see the SAS Enterprise Miner Help.
-
the SAS output from the node.
-
a plot that orders the top 20 variables
by their chi-square statistics. You can also choose to view the top
20 variables ordered by their Cramer's V statistics on this plot.
Tip
In SAS Enterprise
Miner, you can select graphs, tables, and rows within tables and select
Copy from the right-click pop-up menu to copy these items
for subsequent pasting in other applications such as Microsoft Word
and Microsoft Excel.
-
Expand
the Output window, and then scroll to the
Class Variable
Summary Statistics and
Interval Variable Summary
Statistics sections of the output.
-
Notice that there are four variables
for which there are missing values. Later in the example, you will
impute values to use in the place of missing values for these variables.
-
Notice that several variables have
relatively large standard deviations. Later in the example, you will
plot the data and explore transformations that can reduce the variances
of these variables.
-
Close
the Results window.
