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@article{162003,
        author = {Athwika Gade and Snehitha Srinivas  and Ashwanth Dasari and Aswin Manoj and Ayesha Javeriya and Sayeesh . A and Kalyani. A},
        title = {Reviews on crop yield prediction},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {7},
        pages = {203-206},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=162003},
        abstract = {Time series analysis is a technique used to analyze statistical data over a period of time. When predicting future events over an extended period of time, this method is trustworthy and scientific. Time series analysis could always forecast the probability of production almost exactly. The focus of prediction in this work is food production. In this research, logistic regressions and Random Forests are the most popular classification techniques. This research projects crop production over an extended period of time using the proposed ensemble model. The Random Forest and Logistic Regression techniques are contrasted with this ensemble model. The accuracy and the classification error are the two factors that are employed independently for the output prediction.},
        keywords = {Crop yield prediction, Decision trees, Systematic literature review Machine learning, Deep learning},
        month = {},
        }