AGRICULTURAL DATA ANALYSIS

In agriculture sector where farmers and agribusinesses have to make innumerable decisions every day intricate complexities involves the various factors influencing them. An essential issue for agricultural planning intention is accurate yield estimation numerous crops involved in planning. Data mining techniques are necessary approach accomplishing practical effective solutions this problem. Agriculture has been an obvious target big data. Environmental conditions, variability soil, input levels, combinations commodity prices made it all more relevant use information get help critical farming decisions. This paper focuses on analysis of data finding optimal parameters maximize crop production using Machine learning like random forest regressor Linear Regression. Mining large amount existing crop, soil climatic data, analysing new, non-experimental optimizes makes resilient change.