FUN_kernels

<p>performs kernel smoothing using a bandwidth. Besides using a kernel there is also the option to combine kernels</p>

internal

A Non-Metric Space Library ('NMSLIB' <https://github.com/searchivarius/nmslib>) wrapper, which according to the authors "is an efficient cross-platform similarity search library and a toolkit for evaluation of similarity search methods. The goal of the 'NMSLIB' <https://github.com/searchivarius/nmslib> Library is to create an effective and comprehensive toolkit for searching in generic non-metric spaces. Being comprehensive is important, because no single method is likely to be sufficient in all cases. Also note that exact solutions are hardly efficient in high dimensions and/or non-metric spaces. Hence, the main focus is on approximate methods". The wrapper also includes Approximate Kernel k-Nearest-Neighbor functions based on the 'NMSLIB' <https://github.com/searchivarius/nmslib> 'Python' Library.

Lampros Mouselimis

nmslibR

Non Metric Space (Approximate) Library

B. Naidan

L. Boytsov

Yu. Malkov

B. Frederickson

D. Novak

FUN_kernels function

performs kernel smoothing using a bandwidth. Besides using a kernel there is also the option to combine kernels — FUN_kernels

performs kernel smoothing using a bandwidth. Besides using a kernel there is also the option to combine kernels

FUN_kernels: performs kernel smoothing using a bandwidth. Besides using a kernel there is also the option to combine kernels

Description

Usage

Arguments