1Department of Computer Science and Engineering, Acharya Nagarjuna University, Nagarjuna Nagar - 522 510, Andhra Pradesh, India
2Department of Computer Science and Engineering, Sri Venkateswara University College of Engineering, Sri Venkateswara University, Tirupati - 517 502, Andhra Pradesh, India
Large amount of data in agriculture on various crops were collected and stored in simple databases. Tobacco is one of the important commercial crops and the leaf is the economic product. Data collected on various aspects of tobacco production are stored and the required information are retrieved using simple database techniques. In this paper, a classification technique was proposed to classify the data related to tobacco grades which is a prerequisite for fixing the tobacco price. The proposed method modifies the consideration of the decision tree for classification at the data warehousing level by grouping the samples using classification codes (CC) in each branch of the tree. At run time, only the code field and class field were transferred to main memory, which makes effective usage of main memory, despite the database being very large. With this construction, the number of rules to be generated decreased and the number of tests to be performed also decreased which made the execution fast and increased the throughput. The proposed algorithm proves to be effective and efficient
Data mining, algorithm, classification, tobacco, decision tree
