Adaptive and automatic gradient boosting computations.
-
Updated
Aug 20, 2022 - R
Adaptive and automatic gradient boosting computations.
mlim: single and multiple imputation with automated machine learning
🌳 Stacked Gradient Boosting Machines
Machine Learning algorithms coded from scratch
Solution for the Ultimate Student Hunt Challenge (1st place).
mfair: Matrix Factorization with Auxiliary Information in R
Code repository for "A General Machine Learning Framework for Survival Analysis" published at ECML 2020
Extracción de viviendas del portal inmobiliario Idealista. Análisis de efectos geoespaciales en la modelización del precio de la vivienda en la ciudad de Madrid.
Solution for ENS - Societe Generale Challenge (1st place).
Gradient-Boosted Estimation of Generalized Linear Models for Conditional Vine Copulas
One Data Set with multiple Algorithms
Mixtures of Non-Homogenous Linear Regression Models
VMWare-Analytics-Harward-Business-Case-Study-
Reverse engineered the pricing structure of a competitor using machine learning algorithm (Gradient Boosted Trees)
Stroke: Statistical analysis of risk factors and creation of predictive models using machine learning
Reproducing and extending results from PrOCTOR paper (Predicting Odds of Clinical Trial Outcomes using Random forest) via gradient boosting methods
K-means clustering and gradient boosting (XGBoost)
Driven Data Competition
Add a description, image, and links to the gradient-boosting topic page so that developers can more easily learn about it.
To associate your repository with the gradient-boosting topic, visit your repo's landing page and select "manage topics."