Subset K-Means Approach for Handling Imbalanced-Distributed Data

C, Santhosh Kumar; Rao, K. Nageswara; Govardhan, A.; Sandhya, N.

doi:10.1007/978-3-319-13731-5_54

Cited by 5 publications

(3 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

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%

Intervention of data analysis on enterprise crisis management to improve agricultural economy

Yang

2023

J INFORM SYSTEMS ENG

View full text Add to dashboard Cite

The creation of a massive amount of data has allowed for a cutting-edge change in farmed item displaying approaches. According to a research of agricultural item advertising channels, the traditional single rural item showcasing channel has stifled the expansion of the horticultural item market in favour of enterprise crisis management, and there are still intermediary connections in the many promoting channels. The process of showcasing indicates a number of steps taken to get a product from its place of manufacture to its intended usage. It entails all of the processes that result in the utility of time, place, structure, and ownership. develop horticultural goods that encourage the use of enterprise crisis management. This research looked at economic surplus, fractional planning, the economic surplus model, and production function analysis. The amount of the paddy study that was predicted occurred in payment, showing a high rate of earnings for the exploration endeavour. additional funding should be set aside for study into these yields in order to boost ranch pay and asset utilisation, and farmers can be encouraged to use additional assortments. Significant factual measures like rates, frequencies, midpoints, and proper tests were utilized for significant examination and translation of the outcomes. The economic surplus because of VCF-0517 paddy assortment worked out to be Rs.5248 crores for the period from 2006 to 2020. In this all-out economic surplus, the maker surplus framed 56.05 percent and staying 43.95 percent was buyer's surplus.

show abstract

Section: Fractional Planningmentioning

confidence: 99%

Intervention of data analysis on enterprise crisis management to improve agricultural economy

Yang

2023

J INFORM SYSTEMS ENG

View full text Add to dashboard Cite

show abstract

“…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%

Formation and Diffusion Analysis of Agricultural Product Brand Communication Influence Based on Big Data Fuzzy K-Means Clustering in Convergent Media Era

Xiang-yang

2022

Mobile Information Systems

View full text Add to dashboard Cite

In today’s society, with the support of information technology, the media is constantly developing in the direction of integration, which has a profound impact on all aspects of people’s social life. The brand of agricultural products is derived from the definition of brand, based on the differences of production areas, varieties and quality of characteristic agricultural products, and conveyed the information of characteristic agricultural products in the form of trademarks, certification marks, and product packaging. In order to solve the problems existing in the running process of brand promotion system of characteristic agricultural products, the concept of Internet of Things was introduced. The Internet of Things is a network that shows that objects and objects are connected with each other. Customers who use the Internet of Things can communicate and exchange information between any kind of goods. This paper focuses on the content of the improved K-means clustering model based on multibrand communication of agricultural products, expounds the analysis model and scope of agricultural product brand communication, applies the Internet of Things and related technologies to the brand promotion system of characteristic agricultural products, and simulates agricultural product brand communication by using big data fuzzy K-means clustering algorithm. Finally, the calculation of coincidence rate proves that the maximum distance between agricultural product brand communication influence and K-means clustering algorithm is consistent with the JC value of nodes, and the correct rate is as high as 90%. A communication mode that is more in line with the law of brand influence communication of agricultural products.

show abstract

“…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%

Efficient DANNLO Classifier for Multi-class Imbalanced Data on Hadoop

2017

IJMTER

View full text Add to dashboard Cite

Abstract--In recent years, multi-class imbalance data classification is a major problem in big data. In such situations, we focused on developing a new Deep Artificial Neural Network Learning Optimization (DANNLO) Classifier for large collection of imbalanced data.In our proposed work, first the dataset reduction using principal component analysis for dimensionality reduction and initial centroid is computed.Then, parallel hierarchical Pillar k-means clustering algorithm based on MapReduceis usedto partitioning of an imbalanced data set into similar subset, which can improve the computational cost. The resultant clusters are given as input to the deep ANN for learning. In the next stage, deep neural network has been trained using the back propagation algorithm. In order to optimize the n-dimensional weight space, firefly optimization algorithm is used. Attractiveness and distance of each firefly is computed. Hadoop is used to handle these large volumes of variable size data. Imbalanced datasets is taken from ECDC (European Centre for Disease Prevention and Control) repository.The experimental results illustrated that the proposed method can significantly improve the effectiveness in classifying imbalanced data based on TP rate, F-measure, G-mean measures, confusion matrix, precision, recall, and ROC. The experimental results suggests that DANNLO classifier exceed other ordinary classifiers such as SVM and Random forest classifier on tested imbalanced data sets.

show abstract

Subset K-Means Approach for Handling Imbalanced-Distributed Data

Cited by 5 publications

References 13 publications

Intervention of data analysis on enterprise crisis management to improve agricultural economy

Intervention of data analysis on enterprise crisis management to improve agricultural economy

Formation and Diffusion Analysis of Agricultural Product Brand Communication Influence Based on Big Data Fuzzy K-Means Clustering in Convergent Media Era

Efficient DANNLO Classifier for Multi-class Imbalanced Data on Hadoop

Contact Info

Product

Resources

About