Choose a mining model to view, from those in the current mining structure. The mining model will open in its associated viewer.
Choose a viewer to use to explore the selected mining model. You can use the custom viewer, or the Microsoft Generic Content Tree Viewer. You can also use plug-in viewers if available.
Use this area to choose input attributes and values, so that you can later explore how these affect the outcome.
Choose an input attribute from the list. If you leave the selection as the default, <All>, the chart shows a list of all input attributes, ranked by their impact on the predictable attribute.
Choose a value for the input attribute.
Use these controls to choose a predictable attribute and value to analyze and compare in the bar graph. If you do not change the selections, the bar graph compares the top two outcome states.
Choose a predictable attribute. If you did not define the column as a predictable one when you created the model, you cannot add it here.
Choose a state of the predictable attribute to compare to the state that is contained in Value 2.
You can compare any two discrete or discretized values; however, you cannot compare a value to its complement, as you can in other viewers.
Select a state of the predictable attribute to compare to the state that is contained in Value 1.
This part of the Neural Network tab contains an interactive bar graph, which responds to the selections that you made for input and outcome attributes. Because a neural network calculates the likelihood that a particular value influences a particular outcome, you can choose any combination of inputs, and the bar chart will display how that combination affects the pair of outcomes that you are comparing.
Shows the name of the input attribute you selected in Attribute.
Shows the value for the selected input attribute.
Favors <Value 1>
Displays a bar that indicates how much this particular attribute-value combination affects the target outcome chosen in Value 1.
Favors <Value 2>
Displays a bar that indicates how much this particular attribute-value combination affects the target outcome chosen in Value 2.