Tree Menu

Fuzzy decision trees are an extension of classical decision trees [1,14]. They are formed of one root node, which is the tree top or starting point, and a series of other nodes. Terminal nodes are called leaf nodes, or leaves. Each node corresponds to a split on the values of one input variable. This variable is chosen in order to reach a maximum of homogeneity amongst the examples that belong to the node, relatively to the output variable (response variable). This is equivalent to minimizing the entropy. The paths from the root node towards the leaf nodes are easy to interpret as decision rules, strict of fuzzy depending on the nature of the tree.

The tree can be pruned, by transforming a node into a leaf node, if the performance loss is low. This procedure facilitates the tree interpretation. Pruning is based on the performance of the tree equivalent FIS.

Note: the pruned tree may have a better performance than the full tree. as tree building is based on a purity criterion and not directly on a performance criterion.

Fuzzy decision trees proposed in FisPro are based on a fuzzy implementation of the ID3 algorithm [12].


The fuzzy decision tree generation procedure in FisPro needs both a current FIS configuration file and a current data file. The tree building is based on one output only, even if the FIS has several outputs. This output is user chosen.

Output Type

Four cases are possible:

The first three cases use the fuzzy entropy criterion to build the tree, the last one uses a deviance criterion, based on the output value dispersion at each node and is better suited to a regression case.

For a crisp output with the classification option, classes are determined from data, and discrete MFs corresponding to the class labels are assigned to the output. The maximum number of classes is 100.

With the classification option, the majority class is assigned to each node, without it, the average of the node attracted example output is assigned to it.

In the fuzzy output case, the tree summary gives the fuzzy proportions of the node attracted example output for each MF.


If rules are present in the FIS configuration file, they are ignored.


The Generate tree option opens a pop up windows allowing to choose:


The procedure creates one tree or two (if pruning was selected). It opens two windows for each tree:

View tree

This submenu allows to view an existing tree. Two possibilities are offered.

Graph: the viewing window described above.
Table: non graphical viewing, displaying the same information in a table.
It opens the viewing window described above.