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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | A Machine Learning Approach to Smart Farming |
| Authors Name: | Shailaja Udtewar , Prajakta Dagade , Piyush Khatpe , Rohit Shembekar |
| Unique Id: | IJSDR2402024 |
| Published In: | Volume 9 Issue 2, February-2024 |
| Abstract: | Five popular machine learning algorithms are thoroughly compared in this study: Random Forest, Decision Tree, Naive Bayes, K-Nearest Neighbors (KNN), and Logistic Regression. The objective of the study is to assess and compare these algorithms’ performance on various datasets, including factors like accuracy, precision, recall, and F1 score. All algorithms were built, adjusted, and trained in accordance with standard protocols, and experimentation was used to identify performance metrics. The outcomes demonstrate the algorithms’ performance. High-dimensional, complex data sets work well for Random Forest, but Decision Trees are easier to grasp. When analyzing categorical data, Naive Bayes is robust against extraneous characteristics. When local patterns are significant, KNN works well; nevertheless, for binary data, logistic regression becomes an invaluable tool. |
| Keywords: | Machine Learning, Random Forest, Decision Tree, Naive Bayes, K-Nearest Neighbors, Logistic Regression, Comparative Analysis, Performance Metrics. |
| Cite Article: | "A Machine Learning Approach to Smart Farming", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.9, Issue 2, page no.156 - 172, February-2024, Available :http://www.ijsdr.org/papers/IJSDR2402024.pdf |
| Downloads: | 000340262 |
| Publication Details: | Published Paper ID: IJSDR2402024 Registration ID:209974 Published In: Volume 9 Issue 2, February-2024 DOI (Digital Object Identifier): Page No: 156 - 172 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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