Call for Papers:Vol.12 Issue.1

Submission
Last date		 28-Feb-2026
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-12,Issue-1. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  “Mining the large Banking dataset by using K-means, DBSCAN and HAC in WEKA tool”
PaperId: :  18310
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 8 Issue 5 2022
DUI:    16.0415/IJARIIE-18310
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
JYOTIRIET, PHAGWARA
DR. NAVEEN DHILLIONRIET, PHAGWARA

Abstract

COMPUTER ENGINEERING
HAC, K-MEANS, DBSCAN AND WEKA
The unprecedented growth of competition in the banking technology has raised the importance of retaining current customers and acquires new customers so that is important analyzing Customer behavior, which is based on bank databases. Data mining refers to the process of retrieving knowledge by discovering novel and relative patterns from large datasets. Analyzing bank databases for analyzing customer behavior is difficult since bank databases are multi-dimensional, comprised of monthly account records and daily transaction records. Clustering the datasets, assessment and the way of expressing customer’s demands and the provinces of requests should be recognized for providing services to the customers, banks, financial and credit institute. Clustering play an important role in data mining. It can make a group of abstract objects into classes of similar objects. In the clustering, firstly partition the set of data into groups based on data similarity and then assigns the labels to the groups. The overall goal of this research work is to evaluate the performance of HAC, K-means and density based clustering (DBSCAN) data mining algorithms by considering the different data sets. HAC is a method of cluster analysis which seeks to build a hierarchy of clusters. It has bottom-up and top-down approach. K-means clustering to partition n observations into K clusters in which each observation belongs to the cluster with the nearest mean. Density based clusters are the dense areas in the data space separated from each other by sparse areas. The above mentioned objective is achieved by WEKA (Waikato Environment for Knowledge Analysis) machine learning tool as an API (application programming interface). This tool for data pre-processing, clustering, classification and visualization. This research present a comparative analysis for various clustering algorithms. In experiments the effectiveness of algorithms is evaluated by comparing the results on the datasets.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE JYOTI, and DR. NAVEEN DHILLION. "“Mining the large Banking dataset by using K-means, DBSCAN and HAC in WEKA tool”" International Journal Of Advance Research And Innovative Ideas In Education Volume 8 Issue 5 2022 Page 925-931
MLA JYOTI, and DR. NAVEEN DHILLION. "“Mining the large Banking dataset by using K-means, DBSCAN and HAC in WEKA tool”." International Journal Of Advance Research And Innovative Ideas In Education 8.5(2022) : 925-931.
APA JYOTI, & DR. NAVEEN DHILLION. (2022). “Mining the large Banking dataset by using K-means, DBSCAN and HAC in WEKA tool”. International Journal Of Advance Research And Innovative Ideas In Education, 8(5), 925-931.
Chicago JYOTI, and DR. NAVEEN DHILLION. "“Mining the large Banking dataset by using K-means, DBSCAN and HAC in WEKA tool”." International Journal Of Advance Research And Innovative Ideas In Education 8, no. 5 (2022) : 925-931.
Oxford JYOTI, and DR. NAVEEN DHILLION. '“Mining the large Banking dataset by using K-means, DBSCAN and HAC in WEKA tool”', International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 5, 2022, p. 925-931. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/“Mining_the_large_Banking_dataset_by_using_K_means__DBSCAN_and_HAC_in_WEKA_tool”_ijariie18310.pdf (Accessed : ).
Harvard JYOTI, and DR. NAVEEN DHILLION. (2022) '“Mining the large Banking dataset by using K-means, DBSCAN and HAC in WEKA tool”', International Journal Of Advance Research And Innovative Ideas In Education, 8(5), pp. 925-931IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/“Mining_the_large_Banking_dataset_by_using_K_means__DBSCAN_and_HAC_in_WEKA_tool”_ijariie18310.pdf (Accessed : )
IEEE JYOTI, and DR. NAVEEN DHILLION, "“Mining the large Banking dataset by using K-means, DBSCAN and HAC in WEKA tool”," International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 5, pp. 925-931, Sep-Oct 2022. [Online]. Available: https://ijariie.com/AdminUploadPdf/“Mining_the_large_Banking_dataset_by_using_K_means__DBSCAN_and_HAC_in_WEKA_tool”_ijariie18310.pdf [Accessed : ].
Turabian JYOTI, and DR. NAVEEN DHILLION. "“Mining the large Banking dataset by using K-means, DBSCAN and HAC in WEKA tool”." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 8 number 5 ().
Vancouver JYOTI, and DR. NAVEEN DHILLION. “Mining the large Banking dataset by using K-means, DBSCAN and HAC in WEKA tool”. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2022 [Cited : ]; 8(5) : 925-931. Available from: https://ijariie.com/AdminUploadPdf/“Mining_the_large_Banking_dataset_by_using_K_means__DBSCAN_and_HAC_in_WEKA_tool”_ijariie18310.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Unsupervised Contribution-Oriented Learning Model for Social Influence DetectionComputer EngineeringSnehal Mahjaan Download
DESIGN AND IMPLEMENTATION OF A BLUETOOTH-CONTROLLED ROBOTIC CAR USING ARDUINOComputer Mr. Swapnil Sanjay Bafana Download
AI-DRIVEN DEEPFAKE IDENTIFICATION IN REAL TIMEComputer EngineeringPavan Gajanan Bhonde Download
RESQ-BOTComputer Engineering Tiparkar Prathamesh Navnath Download
A Critical Review and Modern Contextualization of the 2009 Distributed Real-Time Computer Network Architecture (DRNA)Computer EngineeringNandishwar EN Download
Block-Chain Based Document Verification System using IPFSComputer EngineeringAkash Santosh Devade Download
A COMPREHENSIVE REVIEW OF DUAL FEATURE-BASED INTRUSION DETECTION SYSTEM FOR IoT NETWORK SECURITYComputer Science and EngineeringShrinidhi Hegde Download
A Deep Learning Framework for Mood-Based Music Recommendation via Facial Expression AnalysisComputer Vaibhav Ashok Bhangare Download
GREEN NETWORKING: ENERGY-EFFICIENT PROTOCOLS AND SUSTAINABLE NETWORK DESIGN: A COMPREHENSIVE REVIEWComputer Science and EngineeringPradeep Nayak Download
DIABETIC RETINOPATHY DETECTION USING MACHINE LEARNINGComputer EngineeringSiddharth Shukracharya Rokade Download
PERSONALITY PREDICTION USING MLComputer EngineeringTanvi Dashrath Bhagat Download
Crop Disease Detectioncomputer Mansi Sunil Sansare Download
NEXT-GEN PLANT DISEASE DIAGNOSIS WITH GEN-AI AND DEEP LEARNINGComputer ScienceGuruprasad K Download
GEN-AI POWERED PIGEON PEA LEAF-DISEASE DETECTION USING DEEP-LEARNING AND COMPUTER-VISIONComputer ScienceRajshekar G Download
GEN-AI POWERED LIVER-DISEASE DETECTION USING DEEP-LEARNING AND COMPUTER-VISIONComputer ScienceDhananjay M Download
12