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@article{155207,
        author = {Dr.S.Erana Veerappa Dinesh and M. Anusuya and M. Vanneeswari},
        title = {MACHINE LEARNING APPROACH FOR INDIAN CROP YIELD PREDICTION},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {1},
        pages = {141-147},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=155207},
        abstract = {In today's world, technology plays a critical part in overcoming challenges and achieving better and maximal results in a variety of fields. The agricultural sector in India has a significant impact on the economy. Agriculture employs half of the country's population. The agriculture business is heavily influenced by its surroundings' natural circumstances, and as a result, it faces a number of difficulties in terms of actual farming techniques. Agriculture techniques in the country are generally ad hoc, and technological advancement is modest. In this industry, effective technology can be employed to boost yield while minimizing the challenges. Farmers typically sow crops based on their market value and potential yield.},
        keywords = {Crop Recommendation, CNN, Data Analysis, Decision tree, Logistic regression, Machine Learning, Random Forest.},
        month = {},
        }