Weather
By Shavar and Gerlof
Significance
• Predicting the weather
creates a huge benefit for
a large amount of people.
• Harsh weather can cause
a disaster in the agrarian
sector, in case of outdoor
events or to civilization in
general, like we have
seen in Asia.
• Therefore it’s crucial to be
able to predict weather
accurately
Problem
• As you’ve seen it can lead to awkward
situations if the weather isnt known before
it takes place.
• In our data set the main goal is to predict if
outdoor sports games would continue
Attributes of our data
Sunny
• Outlook
Overcast
rainy
•
•
•
•
Temperature
Humidity
Windy
Play (whether the sports team plays or
not)
Interesting Patterns
(by analyzing attributes)
• Most of the time the temperature is below
72.4 degrees Fahrenheit
• Almost two times more games are being
played then being cancelled.
• A lot of plays still go on even when its
raining!!
• And even windiness can’t stop players
from playing their outdoor sports
Classification Acc.
• We decided to use a decision tree in order to predict if
the plays would continue or not
• The reliability of this was about 50%, just as it is on TV
as we all know.
Interesting Patterns
(by analyzing classifiers)
• The prediction became more effective by using a more
advanced tree.
• Because of the relatively small amount of attributes,
there couldn’t be found any more patterns.
In Practice
• Predicting the
weather is used a lot
in public already, as
we all know on the
television, and by
analyzing data we
should be able to
refine our methods.