TY - JOUR AU - Beaulah, R.Nancy PY - 2018/02/25 Y2 - 2024/03/29 TI - Performance Analysis of KNN on Different Types of Attributes JF - International Journal of Engineering and Computer Science JA - int. jour. eng. com. sci VL - 7 IS - 02 SE - Articles DO - UR - http://ijecs.in/index.php/ijecs/article/view/3967 SP - 23628-23631 AB - <p>Data Mining is an inter-disciplinary promising field that focuses on access of information useful for high level decisions and also includes Machine Learning. Data Miners evaluate and filter the data as a result and convert the data into useful information. The useful information is converted into knowledge by performing some techniques. The K-Nearest Neighbor (K-NN) algorithm is an instance based learning method that has been widely used in many pattern classification tasks due to its simplicity, effectiveness and robustness. This paper presents a performance comparison of KNN algorithm in various data sets that includes different types of attributes. The results of this paper are achieved using WEKA tool.</p> ER -