Optimized K Nearest Neighbor Classification Algorithm for Weather Prediction
A Zakiuddin Ahmed1, T.Abdul Razak2
1A Zakiuddin Ahmed, Research Scholar, Department of Computer Science, Jamal Mohamed College(Autonomous), Tiruchirapalli, Affiliated to Bharathidasan University, Tiruchirappalli, Tamilnadu, India.
2Dr.T.Abdul Razak, Associate Professor, Dept. of Computer Science, Jamal Mohamed College(Autonomous), Tiruchirappalli, Affiliated to Bharathidasan University, Tiruchirappalli, Tamilnadu, India.
Manuscript received on November 20, 2019. | Revised Manuscript received on November 28, 2019. | Manuscript published on 30 November, 2019. | PP: 7261-7263 | Volume-8 Issue-4, November 2019. | Retrieval Number: D5281118419/2019©BEIESP | DOI: 10.35940/ijrte.D5281.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Weather has a lot of blow in our daily life and also gained researchers concentration due to its enormous effect in the human life. To defend ourselves from weather, we need to predict the weather such as rainfall, humidity and temperature etc. Using classification algorithms, we can predict the weather by using the past datasets. In this research paper, WEKA tool is used to implement classification algorithms for weather forecasting. Machine Learning is an internal part of artificial intelligence, which is used to design algorithms based on the relationships between data and data trends.
Keywords: Machine Learning, KNN, Random Forest, Decision Tree, WEKA, Filtering.
Scope of the Article: Machine Learning.