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A collection of research papers on decision, classification and regression trees with implementations.
Updated
Jul 25, 2021
Python
A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python
Updated
Jun 29, 2021
Python
Multiple Responses Subgroup Identification
Machine learning assignments through the semester in Bogazici University
Updated
Jun 30, 2020
Jupyter Notebook
Correlation between pitchers' weight, height, pitch type, pitch velocity, horizontal, vertical movement and their onset of Tommy John Surgery
Updated
Jul 5, 2021
Jupyter Notebook
Random Forests built on top of rpart, with additional functionality, split functions and probability distributions.
Classification and Regression Tree
Updated
Oct 10, 2020
Jupyter Notebook
[R][Python] Projects from the MBA "Artificial Intelligence and Machine Learning" and others studies in the same field.
Updated
Nov 13, 2019
Jupyter Notebook
Soccer Player Transfer Value Prediction using Scikit-learn
Updated
Mar 13, 2020
Jupyter Notebook
Recursive Partitioning and Regression Trees adapted to Random Forests with more split functions
The thing of beauty in baseball is that each year we have a chance to see players making a leap. Like Jose Bautista, Jose Ramirez, Ben Zobrist, etc. This research aims to find out of these breakout players, the improvement of what stats are more responsible for their WAR and wRC+ gain.
Updated
Jul 5, 2021
Jupyter Notebook
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