The topic relating to abnormal weather captures my attention as I
believe that steps can be taken to curtain the damage that is caused
due to such events. The project is of paramount importance as
storms have become extremely frequent as well as severe in the
United States of America. If the project would be successful, it
would be highly beneficial for thousands of U.S. citizens who are
vulnerable h to deadly storms. The goal is to predict the likelihood
that any given storm will produce casualties, as well as identify the
five primary features that may cause a storm to be deadly. The
analysis involves creating five different predictive models and
tuning those models until at least one of them has a classification
accuracy of 80% or higher as well as a sensitivity of at least 70%.
By achieving an accurate and reliable model, our organization will
be able to identify characteristics of deadly storms at a much faster
rate. This can help to increase the warning times issued for any
storms that occur in the future. Firstly, a geospatial map of the U.S.
is used to determine which states in the country have the highest
risk of being hit by a dangerous storm. Secondly, a time series graph
is used to evaluate the time(s) of the year when life-threatening
storms are most common. These two methods are useful for finding
the locations that are most vulnerable to deadly storms, as well as
the months during which these storms are most likely to appear.
The final component consists of a text mining study (word cloud) on
the storm event descriptions to determine which words are
frequently used to describe dangerous storms. This will allow us to
identify additional warning signs for deadly storms in the future.
