Automated Weather Event Analysis with Machine Learning
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Date
2016-10-28
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
Weather forecasting has numerous impacts in our
daily life from cultivation to event planning. Previous weather
forecasting models used the complicated blend of mathematical
instruments which was insufficient in order to get higher classification rate. In contrast, simple analytical models are wellsuited for weather forecasting tasks. In this work, we focus
on the weather forecasting by means of classifying different
weather events such as normal, rain, and fog by applying
comprehensible C4.5 learning algorithm on weather and climate
features. The C4.5 classifier classifies weather events by building
the decision tree using information entropy from the set of
training samples. We conducted experiments on LA weather
history dataset; from evaluation results, it is revealed that C4.5
classifier classifies weather events with f-score of around 96.1%.
This model also indicates that climate features such as rainfall,
visibility, temperature, humidity, and wind speed are highly
discriminative toward events classification.
Description
Keywords
Weather Events, Forecasting, Machine Learning
Citation
IIUC-ICISET2016-ID-152