Faster, better, smarter ecological niche modeling and species distribution modeling

mlim: single and multiple imputation with automated machine learning

🌲 broom helpers for decision tree methods (rpart, randomForest, and more!) 🌲

🌳 Stacked Gradient Boosting Machines

Using R and machine learning to build a classifier that can detect credit card fraudulent transactions.

Deep Learning for Automatic Differential Diagnosis of Primary Central Nervous System Lymphoma and Glioblastoma: Multi-parametric MRI based Convolutional Neural Network Model

HIV-1 Envelope Sequence Resistance Predictor to 33 Broadly Neutralizing Antibodies

Auto Machine Learning in R

One Data Set with multiple Algorithms

The Effect of the Linux Kernel Page-Table Isolation (KPTI) Patch (Meltdown Vulnerability) on GBMs

Code for paper "Neurodevelopmental hijacking of oligodendrocyte lineage programs drives glioblastoma infiltration"

Modelling Experts Behaviour in Q&A Communities to Predict Worthy Discussion

Building binary predictors on a heavily imbalanced dataset - exercise on policy cross-selling [kaggle]

In this project, exploratory data analysis was used to identify reasons why employees leave and machine learning methods were used predict employee attrition

Single-cell multi-omic profiling of glioblastoma-associated myeloid cells

This project about the GBM classification model on spam email data set and model optimisation.

Detect Credit Card Fraud with Machine Learning in R

Decompose gbm predictions into feature contributions

Random forest and gradient boosting models applied to wearable accelerometer data classify bicep curl form into correct and common error categories.