Abstract
Data mining techniques are widely used to analyze the large amount of data. Classification is an important technique which classifies data of various real world applications. This paper aims to compare the performance of classification algorithms for weather data using Waikato Environment for Knowledge Analysis (WEKA). Performance analysis done using cross fold and training set method. The best algorithm found was J48 Decision Tree classifier with highest accuracy and minimum error as compared to others.
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Panjwani, S., Naresh Kumar, S., Ahuja, L. (2017). Comparative Study of Classification Techniques for Weather Data. In: Singh, M., Gupta, P., Tyagi, V., Sharma, A., Ören, T., Grosky, W. (eds) Advances in Computing and Data Sciences. ICACDS 2016. Communications in Computer and Information Science, vol 721. Springer, Singapore. https://doi.org/10.1007/978-981-10-5427-3_58
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DOI: https://doi.org/10.1007/978-981-10-5427-3_58
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