Comparative Study of Supervised Learning Technique in Context of Soybeans Data

Data mining has become a research area with increasing importance due to its capability of helping end users extract useful information from large databases. With rapid growth in adapting high-technological tools, businesses can now generate and collect massive amount of data, which they could not have done before. The K-Nearest Neighbor, Multilayer Perception methods are significant for Soybeans data. It can be used for predicting future trends of Soybeans craft and is compared on the basis of various parameters like accuracy. The summary of accuracy is shown on the Multilayer Perceptron classifies more accurately (99.85%) compare as other algorithms to the result we come to know that the higher result with multilayer perceptron for Soybeans data.