Analysis of Wheat Production Techniques
Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.8, No. 8)Publication Date: 2019-08-30
Authors : Navjot Kaur; Amrit Kaur;
Page : 1-5
Keywords : Classification; Prediction Analysis; Wheat Production; naïve bayes;
Abstract
Data mining is defined as the process in which useful information is extracted from the raw data. In order to acquire essential knowledge it is essential to extract large amount of data. This process of extraction is also known as misnomer. Currently in every field, there is large amount of data is present and analyzing whole data is very difficult as well as it consumes a lot of time. The prediction analysis is most useful type of data which is performed today. To perform the prediction analysis the patterns needs to generate from the dataset with the machine learning. The prediction analysis can be done by gathering historical information to generate future trends. So, the knowledge of what has happened previously is used to provide the best valuation of what will happen in future with predictive analysis. Crop production analysis is one of the applications of prediction analysis. The techniques which are designed so far the machine learning techniques. The machine learning techniques are applied with the feature extraction. In this paper, the machine learning techniques are reviewed in terms of technical description and outcomes.
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Last modified: 2019-08-22 19:15:01