Volume 8 Issue 2 - March 2017

  • 1. Applications of data mining classification techniques on predicting breast cancer disease

    Authors : Dr. G. Rasitha Banu, Dr.prakash, Ms.illham Bashier, Ms.summera

    Pages : 321-325

    DOI : http://dx.doi.org/10.21172/1.82.043

    Keywords : Data Mining, Breast Cancer, Decision Trees, Classification, Prediction, accuracy, WEKA

    Abstract :

    AbstractBreast cancer is a malignant growth in the breast tissue. Breast cancer is a second leading death among women today after the cervical cancer. If the breast cancer is diagnosed and treated properly then we can save human life. Data mining is a process of finding hidden pattern in huge volumes of databases. It is very useful in healthcare organization. There are several classification algorithms are available in data mining. In our work, we have used data mining classification algorithms namely Zero R, One R, decision stump and J48 to predict breast cancer and performance measures can be analyzed through confusion matrix. In our work, the J48 Algorithm is giving higher accuracy than other algorithms.

    Citing this Journal Article :

    Dr. G. Rasitha Banu, Dr.prakash, Ms.illham Bashier, Ms.summera, "Applications of data mining classification techniques on predicting breast cancer disease ", https://www.ijltet.org/journal_details.php?id=911&j_id=3692, Volume 8 Issue 2 - March 2017, 321-325, #ijltetorg