• Data Set
  
• Result
  

This dataset contains daily weather observations from numerous Australian weather stations. Observations were drawn from numerous weather stations. The daily observations are available at http://www.bom.gov.au/climate/data. Copyright Commonwealth of Australia 2010, Bureau of Meteorology.

There are total 23 features:

Categorical Features

• Date: The date of observation
• Location: The common name of the location of the weather station
• RainToday: Boolean: 1 if precipitation (mm) in the 24 hours to 9am exceeds 1mm, otherwise 0
• WindDir3pm: Direction of the wind at 3pm
• WindDir9am: Direction of the wind at 9am
• WindGustDir: The direction of the strongest wind gust in the 24 hours to midnight

Numerical Features

• MinTemp: The minimum temperature in degrees celsius
• MaxTemp: The maximum temperature in degrees celsius
• Rainfall: The amount of rainfall recorded for the day in mm
• Evaporation: The so-called Class A pan evaporation (mm) in the 24 hours to 9am
• Sunshine: The number of hours of bright sunshine in the day.
• WindGustSpeed: The speed (km/h) of the strongest wind gust in the 24 hours to midnight
• WindSpeed9am: Wind speed (km/hr) averaged over 10 minutes prior to 9am
• WindSpeed3pm: Wind speed (km/hr) averaged over 10 minutes prior to 3am
• Humidity9am: Humidity (percent) at 9am
• Humidity3pm: Humidity (percent) at 3pm
• Pressure9am: Atmospheric pressure (hpa) reduced to mean sea level at 9am
• Pressure3pm: Atmospheric pressure (hpa) reduced to mean sea level at 3pm
• Cloud9am: Fraction of sky obscured by cloud at 9am. This is measured in "oktas", which are a unit of eigths. It records how many eigths of the sky are obscured by cloud. A 0 measure indicates completely clear sky whilst an 8 indicates that it is completely overcast
• Cloud3pm: Fraction of sky obscured by cloud (in "oktas": eighths) at 3pm. See Cload9am for a description of the values
• Temp9am: Temperature (degrees C) at 9am
• Temp3pm: Temperature (degrees C) at 3pm

Target Variable

• RainTomorrow: The target variable. Did it rain tomorrow? (1 = yes, 0 = no )

On test set: I have used Grid Search View with 10 folds to calculate best combinations of parameters.

• Random Forest Classifier: Accuracy = 0.85 and ROC = 0.82
• Logistic Regression: Accuracy = 0.84 and ROC = 0.79