
120 Knowledge Discovery from Data Streams
x 71 69 80 83 70 65 64 72 75 68 81 85 72 75
C + - + - - + - - - - - + + -
Figure 8.2: Illustrative example of the Btree to store sufficient statistics of a
continuous attribute at a leaf.
at which the attribute-value is less than or greater than the cut point. These
counts are the sufficient statistics for almost all splitting criteria. They are
computed with the use of the two data structures maintained in each leaf of
the decision tree. The first data structure is a vector of the classes distribution
over the attribute-values for the examples that reach the leaf.
For each continuous attribute j, the system maintains ...