2023年10月30日 · This repository contains an implementation of the kNN-P classifier, an enhanced version of the k-nearest neighbors algorithm utilizing membrane computing. kNN-P is designed for parallel and distributed computing, which can improve the performance of the original k-nearest neighbors algorithm for classification tasks.

2023年10月30日 · This repository contains an implementation of the kNN-P classifier, an enhanced version of the k-nearest neighbors algorithm utilizing membrane computing. kNN-P is designed for parallel and distributed computing, which can improve the performance of the original k-nearest neighbors algorithm for classification tasks.

The authors present a systolic algorithm and its variations for the k-nearest neighbors problem (kNNP). Multiple-shot queries with different ranges (k values) can be served in a pipelined fashion. A partitioning scheme is developed to handle large size problems.

1992年1月1日 · The algorithm can solve a multiple-shot kNNP in N+2 square root N*K systolic steps using square root N*K processing elements, where N is the problem size (i.e. the number of points), and K is the sum of all k-values.

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In this paper we propose a k-nearest neighbors (kNN) classifier optimized by P systems, called kNN-P, which can improve the performance of the original kNN classifier. A P system consisting of multiple cells is considered as its computational framework. Under the control of both evolution rules and communication rules, each cell determines the optimal set of …

Package ‘knnp’ October 13, 2022 Version 2.0.0 Date 2020-01-10 Title Time Series Prediction using K-Nearest Neighbors Algorithm (Parallel) Depends R (>= 3.6.0) Imports parallelDist, forecast, stats, utils, doParallel, foreach, plyr Suggests tseries, tsibble, datasets Description Two main functionalities are provided. One of them is ...

2020年1月11日 · Creates a matrix to be used for calculating distances. The most recent 'element' is put in the first row of the matrix, the second most recent 'element' in the second row and so on. Therefore, the oldest 'element' is put in the last row. A matrix. Length of each of the 'elements'. A matrix to be used for calculating distances.

2020年1月11日 · knnp: Time Series Prediction using K-Nearest Neighbors Algorithm (Parallel) Two main functionalities are provided. One of them is predicting values with k-nearest neighbors algorithm and the other is optimizing the parameters k and d of the algorithm.