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All Journal International Journal of Artificial Intelligence IJIIS: International Journal of Informatics and Information Systems
Kumar, Akshay
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Computer Science & IT Decision Sciences, Operations Research & Management

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Comparison of Data Normalization for Wine Classification Using K-NN Algorithm Chandra, Rohitash; Chaudhary, Kaylash; Kumar, Akshay
International Journal of Informatics and Information Systems Vol 5, No 4: December 2022
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v5i4.145

Abstract

The range of values that are not balanced on each attribute can affect the quality of data mining results. For this reason, it is necessary to pre-process the data. This preprocessing is expected to increase the accuracy of the results from the wine dataset classification. The preprocessing method used is data transformation with normalization. There are three ways to do data transformation with normalization, namely min-max normalization, z-score normalization, and decimal scaling. Data that has been processed from each normalization method will be compared to see the results of the best classification accuracy using the K-NN algorithm. The K used in the comparisons were 1, 3, 5, 7, 9, 11. Before classifying the normalized wine dataset, it was divided into test data and training data with k-fold cross validation. The division of the data using k is equal to 10. The results of the classification test with the K-NN algorithm show that the best accuracy lies in the wine dataset which has been normalized using the min-max normalization method with K = 1 of 65.92%. The average obtained is 59.68%.
The Different Techniques for Detection of Plant Leaves Diseases Kumar, Akshay; Singh, Ranvijay; Shashidhara; Neha; Thirukrishna
International Journal of Artificial Intelligence Vol 9 No 1: June 2022
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijai-0901.342

Abstract

As we know that Plant disease detection is an interesting field. Plants are the way to live. In our daily life we are completely dependent on plants. There by plants should be taken care. In most of the studies it is been shown that quality of agricultural products shall be reduced due to various components. The plant diseases are such as bacteria, viruses and fungi. The disease in plant leaf restricts the growth of the plant and also destroys its yield. Every time there is the need of expert to identify plant diseases but manual identification is expensive and also time consuming. So, automatic methods are necessary for detection of disease. Through this paper, we have presented a survey on the different methods of plant leaf disease detection.
Co-Authors Chandra, Rohitash Chaudhary, Kaylash Neha Shashidhara Singh, Ranvijay Thirukrishna