Winner Runners up Prediction Classification - an assignment for the Artificial Intelligence Lab course of BSc CSE degree program at AUST

• Windows 10 Pro
• Python 3.6.4
• JetBrains PyCharm 3.4.4
• Anaconda Cloud

As football is a very popular worldwide sport, this work resolves around the different football leagues around the world. It is a classifying problem of predicting the Winners or Runners Ups of a league in a particular season.

The dataset of this problem has been created with the information from the site "World Football" (http://www.worldfootball.com). There are 120 entries in the dataset with fourteen columns. We use the records of four popular League records. They are:

• Premier league
• Bundesliga
• Ligue 1
• La Liga

The columns of the dataset are as such:

• YearFrom : The year a season starts
• YearTo : The year a season ends
• Club : Name of the football club
• Country : The country the club is from
• League : The league of participation
• Pld : Number of games played in the particular season
• W : Number of games won in the particular season
• D : Number of games drawn in the particular season
• L : Number of games lost in the particular season
• GF : Goals scored the club
• GA : Goals scored against the club
• GD : Goal difference
• Points : Points gained by the club in the particular season
• Outcome : If the club was winner or runner up that season

The target column is Outcome.

• Logistic regression
• SGD Classification
• K Nearest Neighbors Classification
• Decision Tree Classification
• Ada Boost Classification
• Random Forest Classification

• Accuracy score
• Precision score
• Recall score
• F1 score