Machine Learning and its Applications in Agriculture. A Predictive Analytics in Agriculture - A Systematic Approach

      Аннотация: Agriculture planning plays a significant role in economic growth and food security of a country. Selection of crops is an important factor in agriculture planning. Farmers usually plan the cultivation process based on their previous experiences. But, due to the lack of precise knowledge about cultivation, they end up cultivating undesirable crops which result in low yield production. So farmers need a Decision Support System (DSS) to make an informal decision that can help farmers in cultivating right crop at the right time under the given conditions. Many researchers try to establish an intelligent predictive system to increase the prediction of yield rate of crops based on the weather and soil using statistical methods. Machine learning is an emerging area and can be used to improve prediction of crop yield under different climatic condition like season, temperature, rainfall etc. Many machine learning techniques can be applied in the prediction process. Classification is a supervised learning technique which can be used to carry out prediction in agriculture sector. This book is all about machine learning and its applications in agricultural field.

Ключевые слова: agriculture, Classification, clustering, crop, Decision Tree, Machine Learning, R, soil