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A machine learning project that applies a Decision Tree Classifier to predict NBA player inductions into the Hall of Fame. Using historical player statistics and performance metrics, the model provides an insightful evaluation of which factors contribute most significantly to a player's likelihood of reaching hof status.

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VictorSquidWei/NBA-HOF-prediction-with-DecisionTreeClassifier

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Victor Wei

Research on NBA class of 2016 Future Hall of Fame Status Prediction Model based on Rookie Season Basic and Advanced Player Statistics

To run the code:

Open the entire folder with VS code
Go to process.py
click run

Guide about the result:

The first printed dataframe was used for testing
The second printed dataframe shows the basic stats for players drafted at 1996
The next printed is the (training set accuracy, 1996 prediction accuracy, and prediction results for class of 1996)
The third printed dataframe shows the basic and advanced stats for players drafted at 1996
The next printed is the (training set accuracy, 1996 prediction accuracy, and prediction results for class of 1996)
The fourth printed dataframe shows the basic and advanced stats for players drafted at 2016
The next printed is the (training set accuracy, prediction results for 2016 class)

Youtube video

https://youtu.be/zAQ_DJz-x3o

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A machine learning project that applies a Decision Tree Classifier to predict NBA player inductions into the Hall of Fame. Using historical player statistics and performance metrics, the model provides an insightful evaluation of which factors contribute most significantly to a player's likelihood of reaching hof status.

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