Online Nonparametric Supervised Learning for Massive Data
Mohamed Chaouch,
Omama M. Al-Hamed
Abstract:Despite their benefits in terms of simplicity, low computational cost and data requirement, parametric machine learning algorithms, such as linear discriminant analysis, quadratic discriminant analysis or logistic regression, suffer from serious drawbacks including linearity, poor fit of features to the usually imposed normal distribution and high dimensionality. Batch kernel-based nonparametric classifier, which overcomes the linearity and normality of features constraints, represents an interesting alternati… Show more
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