Comparison of various classification algorithms on iris datasets using WEKA
| Author(s) | : | Kanu Patel, Jay Vala, Jaymit Pandya |
| Institution | : | |
| Published In | : | Vol. 1, Issue 1 — January 2014 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Classification is one of the most important task of data mining. Main task of datamining is data analysis. For study purpose various algorithm available for classification likedecision tree, Navie Bayes, Back propagation, Neural Network, Artificial Neural, Multi-layerperception, Multi class classification, Support vector Machine, k-nearest neighbor etc. In thispaper we introduce four algorithms from them. Study purpose we take iris.arff dataset.Implement this all algorithm in iris dataset and compare TP-rate, Fp-rate, Precision, Recall andROC Curve parameter. Weka is inbuilt tools for data mining. So we used weka forimplementation.
Kanu Patel, Jay Vala, Jaymit Pandya, “Comparison of various classification algorithms on iris datasets using WEKA”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 1, Issue 1, January 2014.
