TITLE:
Classification of Stateless People through a Robust Nonparametric Kernel Discriminant Function
AUTHORS:
Macdonald G. Obudho, George O. Orwa, Romanus O. Otieno, Festus A. Were
KEYWORDS:
Discriminant Analysis, Kernel Discriminant, Nonparametric, Classification, Statelessness
JOURNAL NAME:
Open Journal of Statistics,
Vol.12 No.5,
October
11,
2022
ABSTRACT: Statelessness is the absence of any Nationality. These include the Pemba,
Shona, Galjeel, people of Burundi and Rwanda descent, and
children born in Kenya to British Overseas Citizens after 1983. Frequently,
they are not only undocumented but also often overlooked and not included in
National Administrative Registers. Accordingly, find it hard to participate in
Social and Economic Affairs. There has been a major push by UNHCR and
international partners to “map” the size of
stateless populations and their demographic profile, as well as causes,
potential solutions and human rights situation. One of the requirements by the
UNHCR in their push is for countries to find a potential solution to statelessness which starts with
classifying/associating a person from these communities to a particular
local community that is recognized in Kenya.
This paper addresses this problem by adopting a Robust Nonparametric Kernel Discriminant function to correctly classify the stateless communities in
Kenya and compare the performance of this method with the existing techniques
through their classification rates. This is because Non-parametric functions
have proven to be more robust and useful especially when there exists auxiliary
information which can be used to increase precision. The findings from this
paper indicate that Nonparametric discriminant classifiers provide a good
classification method for classifying the stateless communities in Kenya. This
is because they exhibit lower classification rates compared to the parametric
methods such as Linear and Quadratic discriminant functions. In addition, the
finding shows that based on certain similarities in characteristics that exist
in these communities that surround the Pemba Community, the Pemba community can
be classified as Giriama or Rabai in which they seem to have a strong link. In
this regard, the study recommends the use of the Kernel discriminant
classifiers in classifying the stateless persons and that the Government of
Kenya consider integrating/recognizing the Pemba community into Giriama or
Rabai so that they can be issued with the National Identification Cards and be
recognized as Kenyans.