Hybrid model of Gradient Boosting Trees and Logistic Regression (GBDT+LR) on Spark

Fast inference of Boosted Decision Trees in FPGAs

Prediction of Breast Cancer using Logistic Regression/Decision Trees/Boosted Decision Trees

📊 Simple Supervised & Unsupervised Machine Learning Models to be applied to Static and Time Series datasets.

Classification Trees, Random Forest, Boosting | Columbia Business School

All the code used for my MSc Thesis: Search for Dark Matter using Machine Learning in dilepton and missing energy events with the ATLAS detector at the LHC, A tentative model independent approach

Research based testing of Boosted Tree Classifier for Predicting Disease from Symptoms

Future Ready Talent Project Submission.Using Azure ML Studio to predict the income of individuals, based on their age, race, education, residence city, etc. Used the adult census dataset

Implementation of decision trees for binary categorical data using numpy. Includes regular decision trees, random forest, and boosted trees.

Making Prediction from fivethirtyeight 2016 Election Poll Data

This is the repository for Jay Shreedhar, Varun Thakur, Tara Gopinath, and Yueyang Pan's final project on diabetes risk classification for DSCI 550 - Data Science At Scale at USC. Check the individual contributor branches for reports on each classification model.

This is the repository for my R project on modeling historical weather data in Santa Barbara.

Codes for reproducing the results of arXiv:2207.04157

A sigmoid SVM classifier for predicting whether an online post is conspiracy or philosophical theory

This is a Credit Analysis project developed by Felipe Solares da Silva and is part of his professional portfolio.

Given financial information of a person, this determines, based on past data (through boosted decision trees), whether or not to approve their loan request.

A R script that runs Boosted Regression Trees(BRT) on epochs of land use datasets with random points to model land use changes and predict and determine the main drivers of change

Machine learning prediction project, R studio, 2019.

Following Project is for predicting the list of creditworthy customers for a bank.

A few classifiers - ML (level basic); scikit-learn