2015
DOI: 10.1007/978-3-319-13731-5_54
|View full text |Cite
|
Sign up to set email alerts
|

Subset K-Means Approach for Handling Imbalanced-Distributed Data

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
2
0

Year Published

2015
2015
2023
2023

Publication Types

Select...
4
1

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(3 citation statements)
references
References 13 publications
0
2
0
Order By: Relevance
“…A straightforward yet incredible asset of halfway planning procedure was utilized to gauge the direct economic advantage (or misfortune) at ranch level by reception of UASB assortments over really look at assortment. This procedure centers around the progressions in pay and costs that would come about because of executing an elective practice or innovation (Kumar et al, 2015). All parts of homestead benefits which stay unaltered by the choice were not thought of.…”
Section: Fractional Planningmentioning
confidence: 99%
“…A straightforward yet incredible asset of halfway planning procedure was utilized to gauge the direct economic advantage (or misfortune) at ranch level by reception of UASB assortments over really look at assortment. This procedure centers around the progressions in pay and costs that would come about because of executing an elective practice or innovation (Kumar et al, 2015). All parts of homestead benefits which stay unaltered by the choice were not thought of.…”
Section: Fractional Planningmentioning
confidence: 99%
“…When Jie studied multidimensional data sets, he concluded that the optimal clustering results can only be achieved when both the objective function and the center point converge at the same time [16]. Kumar explored a method to automatically determine the k value of the cluster center point from the neural network by analyzing the objective function [17]. Yu proposed that distance can be used as a measure of similarity or dissimilarity between objects.…”
Section: Related Workmentioning
confidence: 99%
“…When data become too large difficult to capture, store and manage, the decomposed subsets are grouped together by clustering relate this will fine hidden relationship between the data sets [11]. Big data clustering technique classified into single machine clustering and multiple machine clustering.…”
Section: Introductionmentioning
confidence: 99%