BibTeX:

@article{IJIRSTV4I2054,
     title={Thyroid Data Prediction Using Data Classification Algorithm},
     author={Ammulu and Venugopal },
     journal={International Journal for Innovative Research in Science & Technology},
     volume={4},
     number={2},
     pages={208--212},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV4I2054.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Thyroid is the major disorder occurs due to the lack of thyroid hormone among women than man. The test report of thyroid includes number of attributes such as TSH, T3, TT4, T4U and more. Manually determining the disorder for number of peoples test report is not easier. So, using the data mining approach will made this task simpler by predicting the disorder from the large dataset. Traditionally, Linear Discriminant Analysis (LDA) data mining technique is used to predict the thyroid disorder. In our proposed work, the random forest approach is utilized to predict the hypothyroid disorder by collecting the dataset from UCI repository. The performance measure is calculated from the confusion matrix with the accuracy. The experimental result is obtained from the Weka tool.

Random Forest, thyroid, classification, LDA