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A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python
Unlock profit potential with dynamic pricing! This machine learning project optimizes retail prices using regression trees, delving into price elasticity. Explore tools like Python, Pandas, and Matplotlib for robust analysis and decision-making in this data-driven pricing journey.
The project aims to design machine learning algorithm which is able to predict energy densities of supercapacitors by using input data that is enriched from the results came from image processing techniques.
Kokomo is a competitor robot built for Robocode that uses regression tree based machine learning (called "Dynamic Segmentation" on the Robocode wiki) for its targeting strategy
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.
Progetto universitario volto alla creazione di un programma, che prendendo in input un dataset in forma testuale o da una tabella di un database, genera un albero di regressione per la predizione i dati
Classification And Regression Trees (CART) algorithm is a classification algorithm for building a decision tree based on Gini's impurity index as splitting criterion.