Abstract:
K nearest neighbour classification (KNN)
is a popular non parametric and lazy algorithm for
classification. gaKnn framework is a implementation
of the KNN algorithm combine with genetic
algorithm. It provides genetic algorithm optimization
for KNN algorithm which will optimize the weight
values for each attribute and k value. In this paper, I
proposed improvements for the current
implementation of the gaKnn framework to improve
its usability and performance using kd tree to
improve the KNN algorithm, different data and file
type usage and regression algorithm based on k
nearest neighbour. Mainly it introduce three modules
for the current implementation of the gaKnn
framework namely csv file reader and writer module,
large dataset module and KNN regression module.
