Manuscript received January 3, 2023; revised January 19, 2023; accepted March 12, 2023.
Abstract—Classification is one important area in machine
learning that labels the class of an instance via a classifier from
known-class historical data. One of the popular classifiers is
k-NN, which stands for “k-nearest neighbor” and requires a
global parameter k to proceed. This global parameter may not
be suitable for all instances. Naturally, each instance may
situate on different regions of clusters such as an interior
instance placed inside a cluster, a border instance placed on the
outskirts, an outer instance placed faraway from any cluster,
which requires a different number of neighbors. To
automatically assign a different number of neighbors to each
instance, the concept of scoring from the anomaly detection
research is desired. The Mass-ratio-variance Outlier Factor,
MOF, is selected as the scoring scheme for the number of
neighbors of each instance. MOF gives the highest score to an
instance placed very far from any cluster and the lowest score to
an instance surrounded by other instances. This leads to the
proposed classifier called the conglomerate nearest neighbor
classifier, which does not require any parameter assigning the
appropriate number of neighbors to each instance ordered by
MOF. Experimental results show that this classifier exhibits
similar accuracy to the k-nearest neighbor algorithm with the
best k over the synthesized datasets. Six UCI datasets, the
QSAR dataset, the German dataset, the Cancer dataset, the
Wholesale dataset, the Haberman dataset, and the Glass3
dataset are used in the experiment. This method outperforms
two UCI datasets, Wholesale and Glass3, and displays similar
performance with respect to these six UCI datasets.
Index Terms—Classification, conglomerate nearest neighbor,
-nearest neighbor, and mass-ratio-variance
The authors are with Chulalongkorn University, Bangkok, Thailand.
E-mail: 6470121923@student.chula.ac.th (P.F.)
*Correspondence: krung.s@chula.ac.th (K.S.)
Cite: Patcharasiri Fuangfoo and Krung Sinapiromsaran*, "Parameter-Free Conglomerate nearest Neighbor Classifier Using Mass-Ratio-Variance Outlier Factors," International Journal of Machine Learning vol. 13, no. 4, pp. 158-162, 2023.
Copyright @ 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).