Crop Prediction Model Using Machine Learning Algorithms

Machine learning applications are having a great impact on the global economy by transforming data processing method and decision making. Agriculture is one of fields where significant, considering crisis for food supply. This research investigates potential benefits integrating machine algorithms in modern agriculture. The main focus these to help optimize crop production reduce waste through informed decisions regarding planting, watering, harvesting crops. paper includes discussion current state agriculture, highlighting key challenges opportunities, presents experimental results that demonstrate changing labels accuracy analysis algorithms. findings recommend analyzing wide-ranging collected from farms, incorporating online IoT sensor were obtained real-time manner, farmers can make more verdicts about factors affect growth. Eventually, technologies transform agriculture increasing yields while minimizing waste. Fifteen different have been considered evaluate most appropriate use new feature combination scheme-enhanced algorithm presented. show we achieve classification 99.59% using Bayes Net 99.46% Naïve Classifier Hoeffding Tree These will indicate an increase rates effective cost leading resilient infrastructure sustainable environments. Moreover, this study also future detect diseases early, efficiency, prices when world experiencing shortages.