A NEW APPROACH FOR DATA CLASSIFICATION USING FUZZY LOGIC

被引:0
|
作者
Taneja, Shweta [1 ]
Suri, Bhawna [1 ]
Narwal, Himanshu [1 ]
Jain, Anchit [1 ]
Kathuria, Akshay [1 ]
Gupta, Sachin [1 ]
机构
[1] GGSIPU, BPIT, Dept Comp Sci, New Delhi, India
关键词
Fuzzy C-means (FCM) Algorithm; Fuzzy logic; Classification technique;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Data mining is a process of discovering useful patterns from a large set of data. It is mostly used in large information processing applications. As we know, classification technique of data mining classifies the data into a set of classes based on some attributes for further processing. We have developed a new algorithm to handle the classification by using fuzzy rules on the real world data set. Our proposed algorithm caters in handling admission of students to various universities by classifying them into three clusters-admitted, rejected and those who probably would get the admission. To handle the third cluster, fuzzy logic based approach is appropriate. Our algorithm makes prediction for getting admission on the basis of ranking and fuzzy rules generated from the numerical data and gives output in linguistic terms. We have compared our algorithm with the state of art algorithms-KNN, Fuzzy C- means etc. Our algorithm has proved to be more efficient than others in terms of performance.
引用
收藏
页码:22 / 27
页数:6
相关论文
共 50 条
  • [31] Classification of power disturbances using fuzzy logic
    Bizjak, Boris
    Planinsic, Peter
    [J]. 2006 12TH INTERNATIONAL POWER ELECTRONICS AND MOTION CONTROL CONFERENCE, VOLS 1-4, 2006, : 2001 - +
  • [32] A fuzzy logic approach for the classification of product qualitative characteristics
    Tsekouras, G
    Sarimveis, H
    Raptis, C
    Bafas, G
    [J]. COMPUTERS & CHEMICAL ENGINEERING, 2002, 26 (03) : 429 - 438
  • [33] A Decision Tree Approach to Data Classification using Signal Temporal Logic
    Bombara, Giuseppe
    Vasile, Cristian-Ioan
    Penedo, Francisco
    Yasuoka, Hirotoshi
    Belta, Calin
    [J]. HSCC'16: PROCEEDINGS OF THE 19TH INTERNATIONAL CONFERENCE ON HYBRID SYSTEMS: COMPUTATION AND CONTROL, 2016, : 1 - 10
  • [34] Fuzzy logic approach to multisensor data association
    Chen, YM
    Huang, HC
    [J]. MATHEMATICS AND COMPUTERS IN SIMULATION, 2000, 52 (5-6) : 399 - 412
  • [35] A fuzzy logic modelling approach on psychological data
    Rad, Dana
    Rad, Gavril
    Maier, Roxana
    Demeter, Edgar
    Dicu, Anca
    Popa, Mihaela
    Alexuta, Daniel
    Floroian, Dan
    Marineanu, Vasile Doru
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2022, 43 (02) : 1727 - 1737
  • [36] A new system of a grouting control process using a Fuzzy Logic approach
    Zettler, AH
    Poisel, R
    Stadler, G
    [J]. EUROCK '96/TORINO/ITALY - PREDICTION AND PERFORMANCE IN ROCK MECHANICS AND ROCK ENGINEERING, PROCEEDINGS, VOLS 1 AND 2, 1996, : 1417 - 1424
  • [37] A new approach to the Raw Water Quality Index using the Fuzzy Logic
    de Oliveira, Mariangela Dutra
    Teixeira de Rezende, Oscar Luiz
    Alves Correa Oliveira, Silvia Maria
    Libanio, Marcelo
    [J]. ENGENHARIA SANITARIA E AMBIENTAL, 2014, 19 (04) : 361 - 372
  • [38] Evidence-Theoretic Reentry Target Classification Using Radar: A Fuzzy Logic Approach
    Jung, Kwangyong
    Min, Sawon
    Kim, Jeongwoo
    Kim, Nammoon
    Kim, Euntai
    [J]. IEEE ACCESS, 2021, 9 : 55567 - 55580
  • [39] A pattern recognition approach to robust voiced/unvoiced speech classification using fuzzy logic
    Beritelli, F
    Casale, S
    Russo, M
    [J]. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 1999, 13 (01) : 109 - 132
  • [40] Online approach for Diabetes Diagnosis and Classification with Expert System Modules using Fuzzy Logic
    Mujawar, I. K.
    Jadhav, B. T.
    Waghmare, V. B.
    Patil, R. Y.
    [J]. 2019 IEEE PUNE SECTION INTERNATIONAL CONFERENCE (PUNECON), 2019,