Methods for increasing generalization ability based on different ways of ensembles building
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Updated
Apr 21, 2020 - C++
Methods for increasing generalization ability based on different ways of ensembles building
Decision Tree Classifier and Boosted Random Forest
The code of AAAI20 paper "Efficient Inference of Optimal Decision Trees"
Decision_tree module for C++ and Python
Decision Tree and Perceptron performance comparison through a small dataset
c++ incremental decision tree
Random Forest library university project
Pope is a bot created to play a simplified version of the game "Papers, Please". The name of this AI was given in honor of the game creator Lucas Pope.
This repository provides a C++ implementation for managing missing clinical data using KNN Imputation and building a Decision Tree Classifier. The code allows for estimation of missing values from a dataset and construction of a classifier to categorize subjects as positive or negative cases, based on their clinical features.
Machine learning library for classification tasks
A library to train, evaluate and make inference using random forests.
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