Effects of distance measure choice on k-nearest neighbor classifier performance: a review
HA Abu Alfeilat, ABA Hassanat, O Lasassmeh… - Big data, 2019 - liebertpub.com
The K-nearest neighbor (KNN) classifier is one of the simplest and most common classifiers,
yet its performance competes with the most complex classifiers in the literature. The core of …
yet its performance competes with the most complex classifiers in the literature. The core of …
Distance and similarity measures effect on the performance of K-nearest neighbor classifier--a review
VB Prasath, HAA Alfeilat, A Hassanat… - arXiv preprint arXiv …, 2017 - arxiv.org
The K-nearest neighbor (KNN) classifier is one of the simplest and most common classifiers,
yet its performance competes with the most complex classifiers in the literature. The core of …
yet its performance competes with the most complex classifiers in the literature. The core of …
kNN-IS: An Iterative Spark-based design of the k-Nearest Neighbors classifier for big data
Abstract The k-Nearest Neighbors classifier is a simple yet effective widely renowned
method in data mining. The actual application of this model in the big data domain is not …
method in data mining. The actual application of this model in the big data domain is not …
A novel extreme learning machine based kNN classification method for dealing with big data
Abstract kNN algorithm, as an effective data mining technique, is always attended for
supervised classification. On the other hand, the previously proposed kNN finding methods …
supervised classification. On the other hand, the previously proposed kNN finding methods …
Büyük veri analizinde yapay zekâ ve makine öğrenmesi uygulamalari-artificial intelligence and machine learning applications in big data analysis
Bilgi teknolojilerinde yüksek hızda yaşanan gelişmeler ve internet kullanımının çok yaygın
hale gelmesi ile birlikte, çeşitli platformlarda biriken verinin çeşitliliği ve hacmi de artmıştır …
hale gelmesi ile birlikte, çeşitli platformlarda biriken verinin çeşitliliği ve hacmi de artmıştır …
[HTML][HTML] A new COVID-19 detection method from human genome sequences using CpG island features and KNN classifier
Various viral epidemics have been detected such as the severe acute respiratory syndrome
coronavirus and the Middle East respiratory syndrome coronavirus in the last two decades …
coronavirus and the Middle East respiratory syndrome coronavirus in the last two decades …
A survey of big data architectures and machine learning algorithms in healthcare
G Manogaran, D Lopez - International Journal of …, 2017 - inderscienceonline.com
Big Data has gained much attention from researchers in healthcare, bioinformatics, and
information sciences. As a result, data production at this stage will be 44 times greater than …
information sciences. As a result, data production at this stage will be 44 times greater than …
[HTML][HTML] Fast semistochastic heat-bath configuration interaction
This paper presents in detail our fast semistochastic heat-bath configuration interaction
(SHCI) method for solving the many-body Schrödinger equation. We identify and eliminate …
(SHCI) method for solving the many-body Schrödinger equation. We identify and eliminate …
A survey on classifying big data with label noise
JM Johnson, TM Khoshgoftaar - ACM Journal of Data and Information …, 2022 - dl.acm.org
Class label noise is a critical component of data quality that directly inhibits the predictive
performance of machine learning algorithms. While many data-level and algorithm-level …
performance of machine learning algorithms. While many data-level and algorithm-level …
Distributed nearest neighbor classification for large-scale multi-label data on spark
Modern data is characterized by its ever-increasing volume and complexity, particularly
when data instances belong to many categories simultaneously. This learning paradigm is …
when data instances belong to many categories simultaneously. This learning paradigm is …