Adaptive and automatic gradient boosting computations.
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Updated
Aug 20, 2022 - R
Adaptive and automatic gradient boosting computations.
🌳 Stacked Gradient Boosting Machines
mlim: single and multiple imputation with automated machine learning
Machine Learning algorithms coded from scratch
Code repository for "A General Machine Learning Framework for Survival Analysis" published at ECML 2020
Solution for the Ultimate Student Hunt Challenge (1st place).
mfair: Matrix Factorization with Auxiliary Information in R
Solution for ENS - Societe Generale Challenge (1st place).
Extracción de viviendas del portal inmobiliario Idealista. Análisis de efectos geoespaciales en la modelización del precio de la vivienda en la ciudad de Madrid.
VMWare-Analytics-Harward-Business-Case-Study-
One Data Set with multiple Algorithms
Replication files for "Combining forecasts: Can machines beat the average?" by Tyler Pike and Francisco Vazquez-Grande.
Reverse engineered the pricing structure of a competitor using machine learning algorithm (Gradient Boosted Trees)
Tools created for machine learning classification model evaluation
Reproducing and extending results from PrOCTOR paper (Predicting Odds of Clinical Trial Outcomes using Random forest) via gradient boosting methods
Driven Data Competition
Implementing Gradient Boosting & SuperLearner in R and compare the classification accuracy of the two methods.
Detect Credit Card Fraud with Machine Learning in R
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