In general, the root node is a variable with the highest information gain, whereas the other internal nodes provide the second and subsequent highest information gain thereafter.
As expected, corners have the highest information gain followed by edges and surfaces.
The node with the highest information gain is the root node, and the preceding node with the next highest information gain is selected as the test for the next node.
The attribute with the highest information gain is chosen as the attribute for the current node, and the instances are partitioned accordingly.
See Appendix "Attribute selection based on the information gain method" for information on the numbers of selected attributes and the attributes with highest information gain value.
Constructing a decision tree is all about finding a block as well as a selector that returns the highest information gain.
In each table, the top five attributes with the highest information gain value for each one of the three settings of the tests (1B, 2B, and 3B) are presented, where attribute selection is performed.
We defined four feature sets, one consists of sequence motifs combined with k-mers (284 features) of which 100 features with highest information gain were used during model training, the second is a combination of IT features with k-mers (175 features), the third comprises of IT features (91 features), and the last considered only k-mers (84 features).
The best attribute has the highest information gain.
The SNP with the highest information gain in RA is rs9275418, which is also part of the MHC region, and is strongly associated with both RA (P-value of 1.00 × 10−48) and T1D (P-value of 7.36 × 10−126).
To investigate this we plotted LD 13), the divergence feature with the highest information gain, against Hphob, #neg and the arginine composition (the three highest scoring standard features in the 40 residue N-terminal region).
