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# PERFORMANCE ANALYSISMethod of analysis Crop yield prediction can help agricultural departments to

Categories: HelpScience

4. PERFORMANCE ANALYSISMethod of analysis :Crop yield prediction can help agricultural departments to have strategies for improving agriculture. Crop production depends on climatic, geographical, biological, political and economic factors. Because of these factors there are some risks, which can be quantified when applied appropriate mathematical or statistical methodologies. Actually accurate information about the nature of historical yield of crop is important modeling input, which are helpful to farmers & Government organization for decision making process in establishing proper policies. In this paper we have intend to propose a method for crop yield prediction using classifier.

The proposed crop yield prediction consists of three phases namely, preprocessing, feature reduction and prediction. Here the proposed method use input data as real world data. Real world data is often incomplete, inconsistent, and/or lacking in certain behaviors or trends, and is likely to contain many errors. Data pre-processing is a proven method of resolving such issues. A good data preprocessing helps to create better model and will consume less time.

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Next phase of the proposed method is feature reduction; here we use multilinear principal component analysis (MPCA) for feature reduction phase. Finally the proposed method is use to predict the crop yield by means of regression. The performance of the proposed method is evaluated by prediction accuracy and error value.4.1.Regression:Regression analysis is a form of predictive modelling technique which investigates the association between a dependent (targets) and autonomous variable (s) (independent variables).Linear regression:Linear regression is a linear methodology for demonstrating the link between a scalar dependent variable y and one or more independent variables denoted X.

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