Figure 1
From: Large-scale prediction of long disordered regions in proteins using random forests
A sample random forest. In the decision tree on the left, the node at the root tests an attribute, such as the first order auto-correlation function of the normalized flexibility parameters (see below). If it is higher than a given threshold then the residue is in a disordered state (the right branch labelled D); otherwise another input attribute is tested and a set of other tests are further performed until a decision is made. A random forest can comprise hundreds of decision trees.