文章基本信息

标题：CROP PRODUCTION-ENSEMBLE MACHINE LEARNING MODEL FOR PREDICTION
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作者：N.Naveen Kumar ; P.Mohanraj ; S.Priyatharsini 等
期刊名称：International Journal of Early Childhood Special Education
电子版ISSN：1308-5581
出版年度：2022
卷号：14
期号：4
页码：391-400
DOI：10.9756/INT-JECSE/V14I4.49
语种：English
出版社：International Journal of Early Childhood Special Education
摘要：Information Mining is the most extreme conceivable technique for the predominant virtual worldwide for perusing mass of records units to acquire left out relationship. The methodology utilized for assessing measurable records over a time period is the time assortment assessment. This technique is clinical and reliable in deciding events to see over a period. Likelihood of assembling ought to constantly be supposed to the near flawlessness with the guide of utilizing time assortment assessment. In this work, dinner fabricating is the pushed-for expectation. The recognized sort techniques in this investigation are the Linear Regression (LR) and Naive Bayes. In the Linear Regression and Naive are the proposed outfit adaptation used to task the harvest fabricating over a time period. This troupe adaptation is when contrasted with Linear Regression and Naive Bayes techniques. The boundaries involved each in turn for the forecast of the result are the exactness and the sort of blunder. The finding yields that Linear Regression and Naive are more pleasing than Linear Regression and Naive Bayes for the records set broken down.
关键词：Data Mining;Time Series;Crop Yield Prediction;Linear Regression;Naive Bayes