Call for Paper

CAE solicits original research papers for the April 2023 Edition. Last date of manuscript submission is March 31, 2023.

Read More

Predicting Thyroid Disease using Linear Discriminant Analysis (LDA) Data Mining Technique

G. Rasitha Banu. Published in Information Sciences.

Communications on Applied Electronics
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: G. Rasitha Banu

Rasitha G Banu. Article: Predicting Thyroid Disease using Linear Discriminant Analysis (LDA) Data Mining Technique. Communications on Applied Electronics 4(1):4-6, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

	author = {G. Rasitha Banu},
	title = {Article: Predicting Thyroid Disease using Linear Discriminant Analysis (LDA) Data Mining Technique},
	journal = {Communications on Applied Electronics},
	year = {2016},
	volume = {4},
	number = {1},
	pages = {4-6},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}


Thyroid disease is very common disease in human. Nowadays most of the women suffering from thyroid disease than male. There are two types in thyroid disease like hypothyroid and hyperthyroid disease. These diseases giving many side effects such as weight gain, weight loss, stress and so on to our human body .If this disease is detected in earlier stage, then physician can give proper treatment to the patients .Data Mining is playing important role in predicting many diseases. Classification is one the most significant Technique in Data Mining. It is a supervised learning. It is used to classify predefined data sets. Health care data are having exponential growth in volume and complexity. Data mining Technique is mainly used in healthcare organizations for decision making, diagnosing disease and giving better treatment to the patients. In this paper hypothyroid disease is to be predicted using data mining. The dataset used for the study on hypothyroid is taken from UCI repository. Classification of this thyroid disease is a considerable task. An experimental study is carried out using Linear Discriminant Analysis (LDA) to achieve better accuracy. There are many data mining classification Algorithms such as CART, REP Tree, and J48 and so on. The LDA Algorithm gives accuracy is 99.62% with cross validation k=6.


  1. Jiawei Han, Kamber Micheline (2009). Data mining: Concepts and Techniques, Morgan Kaufmann Publisher.
  2. Paper 094-2010 Building Decision Trees from Decision Stumps Murphy Choy, University College Dublin Peter Flom, Peter Flom Consulting
  3. “UCI Machine Learning Repository of machine learning database”, University of California, school of Information and Computer Science, Irvine. C.A.
  5. Dr. G. Rasitha Banu, Baviya “A study on Thyroid disease using Data Mining Technique”, IJTRA Journal, aug 2015.
  6. Dr .G .Rasitha Banu, Baviya “ predicting Thyroid disease using Data Mining Technique “, IJMTER journal, March 2015.
  7. Pandey, Rohit Miri , Tandan ”Diagnosis And Classification Of Hypothyroid Disease Using Data Mining”, International Journal of Engineering Research & Technology (IJERT),Vol. 2 Issue 6, June – 2013
  8. D .Lavanya, Dr .Usha Rani, ” Performance Evaluation of Decision Tree Classifiers on Medical Datasets”, International Journal of Computer Applications (0975 – 8887),Volume 26– No.4, July 2011
  9. K. Saravana Kumar, Dr. R. Manicka Chezian “Support Vector Machine And K- Nearest Neighbor Based Analysis For The Prediction Of Hypothyroid”, International Journal of Pharma and Bio Sciences.,
  10. Prerana, Parveen Sehgal, Khushboo Taneja “Predictive Data Mining for Diagnosis of Thyroid Disease using Neural Network”, International Journal of Research in Management, Science & Technology (E-ISSN: 2321-3264) Vol. 3, No. 2, April 2015.
  11. J. Han and M. Kamber, Data Mining Concepts and Techniques, Elsevier, Australia, 2006


Thyroid disease, classification, Linear Discriminant Analysis, Decision tree