SBL-PM-E and SBL-PM-M: New Methods for Partial Memory Learning
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چکیده
Partial Memory Learning (PML) is a machine learning paradigm in which only subset of a training set is used during learning. This paper concerns new methods for partial memory learning. The SBL-PM-E method is an extension of the SBL-PM algorithm developed by us earlier. The SBL-PM-M method is however a completely new model. We evaluate the performance of the new algorithms on several real-world datasets and compare them to the original SBL-PM algorithm. keywords: classification, machine learning, partial-memory learning
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تاریخ انتشار 2003