Classification of SOA-Based Cloud Services Using Data Mining Technique

2020 ◽  
pp. 971-978
Author(s):  
Zeenat Parween ◽  
R. B. S. Yadav
Keyword(s):  
Data Mining ◽  
Cloud Services ◽  
Data Mining Technique ◽  
Mining Technique ◽  
Using Data

scholarly journals Classification of Hematological Data Using Data Mining Technique to Predict Diseases

2018 ◽  
Vol 06 (04) ◽  
pp. 76-83 ◽  
Author(s):  
Fahmida Akter ◽  
Md Altab Hossin ◽  
Golam Moktader Daiyan ◽  
Md. Motaher Hossain
Keyword(s):  
Data Mining ◽  
Data Mining Technique ◽  
Mining Technique ◽  
Using Data

scholarly journals Implementation of Hospital Examination Reservation System Using Data Mining Technique

2015 ◽  
Vol 21 (2) ◽  
pp. 95
Author(s):  
Hyo Soung Cha ◽  
Tae Sik Yoon ◽  
Ki Chung Ryu ◽  
Il Won Shin ◽  
Yang Hyo Choe ◽  
...  
Keyword(s):  
Data Mining ◽  
Data Mining Technique ◽  
Mining Technique ◽  
Reservation System ◽  
Using Data

scholarly journals Analysis on Insurance Policy and Related Customer Behavior using Data Mining Technique

2016 ◽  
Vol 139 (6) ◽  
pp. 46-47
Author(s):  
M. Ashrafa ◽  
D. Asha ◽  
D. Radha ◽  
M. Sangeetha ◽  
R. Jayaparvathy
Keyword(s):  
Data Mining ◽  
Customer Behavior ◽  
Insurance Policy ◽  
Data Mining Technique ◽  
Mining Technique ◽  
Using Data

scholarly journals Techniques for Image Segmentation: A Critical Review

2021 ◽  
Vol 9 (3) ◽  
pp. 1-4
Author(s):  
Harshita Mishra ◽  
Anuradha Misra
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Image Segmentation ◽  
Digital Image ◽  
Electronic Devices ◽  
Data Mining Technique ◽  
Mining Technique ◽  
Mathematical Algorithms ◽  
Picture Element

In today’s world there is requirement of some techniques or methods that will be helpful for retrieval of the information from the images. Information those are important for finding solution to the problems in the present time are needed. In this review we will study the processing involved in the digitalization of the image. The set or proper array of the pixels that is also called as picture element is known as image. The positioning of these pixels is in matrix which is formed in columns and rows. The image undergoes the process of digitalization by which a digital image is formed. This process of digitalization is called digital image processing of the image (D.I.P). Electronic devices as such computers are used for the processing of the image into digital image. There are various techniques that are used for image segmentation process. In this review we will also try to understand the involvement of data mining for the extraction of the information from the image. The process of the identifying patterns in the large stored data with the help of statistic and mathematical algorithms is data mining. The pixel wise classification of the image segmentation uses data mining technique.

scholarly journals Impact of Data Mining Technique in Education Institutions

2015 ◽  
Vol 4 (02) ◽  
pp. 01-07
Author(s):  
Mr. Bhushan Bandre, Ms. Rashmi Khalatkar
Keyword(s):  
Data Mining ◽  
Educational Institution ◽  
Educational Institutions ◽  
Data Mining Technique ◽  
Admission Process ◽  
Data Mining Techniques ◽  
Mining Technique ◽  
Major Parameter ◽  
Using Data ◽  
Major Decision

Major decision making process using large amount of data can be done by various techniques using data mining. In education sectors various data mining techniques are implemented to analyze the student’s data from the admission process itself. Due to large number of educational institution in India, excellence becomes a major parameter for the institutions to grow and with stand. Nowadays education institutions use data mining techniques to show their excellence. The main objective of this work to present an analysis of individual semester wise results of engineering college students using different techniques of data mining. Here we used different classification algorithms like decision tree, rule based, function based and Bayesian algorithms to analyze the semester results and comparison is made by considering parameters like accuracy and error rate. Our output shows the most suited algorithm for analyzing data in educational institutions.

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