Boosting Functional Regression Models. The current release version can be found on CRAN (http://cran.r-project.org/package=FDboost).

Decision Trees, Bagging and Boosting

Problem Sets and Final Exam for Texas A&M ECMT 670: Machine Learning in Econometrics

Distributed component-wise boosting using DataSHIELD

Introduction to three machine learning models using the programming language R

Capstone project for my Master's degree. In it, I developed some machine learning models to predict the heat of formation for materials containing 1–3 components.

Work I did for a group project that built machine learning models for heart disease datasets.

This project aims to analyze the heart failure dataset to build a classifier that identifies the most important factors and allows predicting death from heart failure.

Classification of Obesity Status in Indonesia Using XGBoost & ADASYN-N Method

This project has the aim to analyze the Heart Disease dataset to build a classifiers to predict whether people have heart disease or not.

Solution for ENS - Societe Generale Challenge (1st place).

Forecast of car claim frequency using GLM, boosting and neural networks

An R Package with Boosting and SMOTEBoost implementations for Regression Tasks

This is where I'll post my machine learning templates that I've created

Parkinson’s disease classification using speech signal features; comparison of various multiclass classification algorithms

Использование методов машинного обучения для прогнозирования инвестиций в России

Data Analytics and Machine Learning in R. Linear-regression, Logistic-regression, Hierarchical-clustering, Boosting, Bagging, Random-forests, K-means-clustering, K-nearest-neighbors (K-N-N), Tree-pruning, Subset-selection, LDA, QDA, Support Vector Machines (SVM)

A data set of 30000 records and 24 variables containing information on defaults, demographic factors, credit data, delinquency, repayment and billed amounts of a credit card client in Taiwan from April 2005 to September 2005. The objective was to apply statistical, data visualization and Machine learning techniques (supervised and unsupervised) …