The experimental results show that the proposed algorithm performs better than the original Winnow and the representative improved Winnow algorithms ...
The experimental results show that the proposed algorithm performs better than the original Winnow and the representative improved Winnow algorithms.
An adaptive improved Winnow algorithm is presented, the main improvements are the adaptive selection of block size and a new uniform random scrambling ...
Jul 1, 2015 · In this paper, an adaptive improved Winnow algorithm is presented, the main improvements are the adaptive selection of block size and a new ...
Request PDF | On Jul 1, 2015, Qiong Li and others published An Adaptive Improved Winnow Algorithm | Find, read and cite all the research you need on ...
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What is the winnowing algorithm?
How do the Perceptron and Winnow algorithms compare?
A Canonical Variate Feature Selection based Adaptive Enhanced Winnow Map Reduce Classification (CVFS-AEWMRC) Method is proposed.
In this paper, we derive regularized Winnow methods by constructing “optimal hyperplanes” that minimize the Winnow mistake bound (rather than the Perceptron ...
Jul 30, 2024 · Unlike the Perceptron algorithm, Winnow employs a multiplicative weight update function, which leads to fewer mistakes and faster convergence.
The Winnow Algorithm is a supervised learning algorithm designed for binary classification, particularly effective for high-dimensional and sparse datasets.
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This paper presents an algorithm for incremental induction of decision trees that is able to handle both numeric and symbolic variables.