Data Mining Techniques for Identification and Classification of Various Diseases in Plants
Arun Kumar Nakatha1, Sathish S. Kumar2

1Arun Kumar Nakatha, Research Scholar, Department of Computer Science and Engineering, RNS Institute of Technology, Bengaluru (Karnataka), India.

2Dr. Sathish S. Kumar, Professor, Department of Information Science and Engineering, RNS Institute of Technology, Bengaluru (Karnataka), India.

Manuscript received on 09 December 2019 | Revised Manuscript received on 17 December 2019 | Manuscript Published on 31 December 2019 | PP: 676-680 | Volume-9 Issue-2S December 2019 | Retrieval Number: B11101292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1110.1292S19

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Abstract: Data mining is currently being used in various applications; In research community it plays a vital role. This paper specify about data mining techniques for the preprocessing and classification of various disease in plants. Since various plants has different diseases based on that each of them has different data sets and different objectives for knowledge discovery. Data Mining Techniques applied on plants that it helps in segmentation and classification of diseased plants, it avoids Oral Inspection and helps to increase in crop productivity. This paper provides various classification techniques Such as K-Nearest Neighbors, Support Vector Machine, Principle component Analysis, Neural Network. Thus among various techniques neural network is effective for disease detection in plants.

Keywords: Classification, Data Mining, K-Nearest Neighbors, Neural Network, Preprocessing, Principle Component Analysis, Segmentation, Support Vector Machine.
Scope of the Article: Data Mining