Crop Yield Prediction In Machine Learning Using RapidMiner Tool

Abstract

Harvesting is a completely essential problem in
agriculture. Machine learning is a critical subject of emerging
research in crop yield evaluation. During the last decade, the
climate has modified dramatically. Because of this, the farmers
who were planting traditional crops are now facing problems. It
is important that if farmers know the yield of the crop, they are
planting in advance so that they can choose a crop that will suit
their region. Analyzing various attributes such as season, crop
type and area, will help farmers to know how much the crop will
yield before harvest. The purpose of this paper is to help the
farmer determine which crop will suit his region by predicting
the yield of the crop. Machine learning is an important way to
experience reality to overcome this problem. With the help of
RapidMiner tool, Linear regression algorithm is used to train the
model to get accurate predictions