There is growing interest in scaling up the widely-used decision-tree learning algorithms to very large data sets. Although numerous diverse techniques have been proposed, a fast ...
straction is a useful tool for agents interacting with environments. Good state abstractions are compact, reuseable, and easy to learn from sample data. This paper and extends two...
It hasbeenshownthat a neuralnetworkis better thana direct applicationof inductiontrees in modelingcomplex relations of inputattributes in sampledata. We proposethat conciserules b...