This paper surveys locally weighted learning, a form of lazy learning and memory-based
learning, and focuses on locally weighted linear regression. The survey discusses distance …

Many lazy learning algorithms are derivatives of the k-nearest neighbor (k-NN) classifier,
which uses a distance function to generate predictions from stored instances. Several …

Long-duration energy storage (LDES) is a potential solution to intermittency in renewable
energy generation. In this study we have evaluated the role of LDES in decarbonized …

Polyploidy is an evolutionary innovation for many animals and all flowering plants, but its
impact on selection and domestication remains elusive. Here we analyze genome evolution …

There is growing evidence of escalating wildlife losses worldwide. Extreme wildlife losses
have recently been documented for large parts of Africa, including western, Central and …

Statistical methods for handling circular data have developed rapidly in the past twenty
years, with emphasis on problems of data display, and the correlation, regression, and …

Hidden Markov models—most often abbreviated to the acronym “HMMs”—are one of the
most successful statistical modelling ideas that have came up in the last forty years: the use …

R is rapidly growing in popularity as the environment of choice for data analysis and
graphics both in academia and industry. Lattice brings the proven design of Trellis graphics …

Semiparametric regression is concerned with the flexible incorporation of non-linear
functional relationships in regression analyses. Any application area that benefits from …

The existence of high speed, inexpensive computing has made it easy to look at data in
ways that were once impossible. Where once a data analyst was forced to make restrictive …