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Benchm Ml ⭐ 1,839

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

Parsnip ⭐ 546

A tidy unified interface to models

Advanced High Performance Data Science Toolbox for R by Laurae

Machine Learning algorithms for spatial and spatiotemporal data

Ggrandomforests ⭐ 133

Graphical analysis of random forests with the randomForestSRC, randomForest and ggplot2 packages.

Forester ⭐ 123

An R package for creating publication-ready forest plots.

Random forests for R for large data sets, optimized with parallel tree-growing and disk-based memory

Official Git repository of R package meta

exploratory data analysis using random forests

Randomforestci ⭐ 58

This package is DEPRECATED. Please use the packages `grf` or `ranger` instead, which have built-in confidence intervals.

Missranger ⭐ 53

R package "missRanger" for fast imputation of missing values by random forests.

Trait-Driven Models of Ecology and Evolution 🌲

Foresttools ⭐ 49

Detect and segment individual tree from remotely sensed data

Miceranger ⭐ 42

miceRanger: Fast Imputation with Random Forests in R

Mlbayesopt ⭐ 39

R package to tune parameters for machine learning(Support Vector Machine, Random Forest, and Xgboost), using bayesian optimization with gaussian process

Forestplot ⭐ 37

Advanced forest plots in R using grid graphics

Forestfloor ⭐ 35

R package to visualize mapping structures of random forests with feature contributions

Forestmodel ⭐ 30

Causalforest ⭐ 30

DEPRECATED. See new generalized random forest package for up-to-date implementation.

Coveffectsplot ⭐ 29

A Shiny App that Produce Forest Plots to Visualize Covariate Effects

Machine_learning ⭐ 27

Machine learning in R

iterative Random Forests (iRF): iteratively grows weighted random forests, finds interaction among features

Forestgapr ⭐ 26

ForestGapR: An R Package for Airborne Laser Scanning-derived Tropical Forest Gaps Analysis

Tuneranger ⭐ 25

Automatic tuning of random forests

Variable Selection Using Random Forests

A random-forest-based approach for imputing clustered incomplete data

Canopylazr ⭐ 22

R package to estimate leaf area density (LAD) and leaf area index (LAI) from airborne LiDAR point clouds

Lidrplugins ⭐ 22

Extra functions and algorithms for lidR package

Brmstools ⭐ 22

Helper functions for brmsfit objects (DEPRECATED)

Foresterror ⭐ 22

A Unified Framework for Random Forest Prediction Error Estimation

Statistical methods for forest genetic resources analysts

Solitude ⭐ 19

An implementation of Isolation forest

Gfcanalysis ⭐ 17

Tools for working with Hansen et al. Global Forest Change dataset

Pathogenicity prediction of bacterial genomes

Rotationforest ⭐ 17

An implementation of the Rotation Forest algorithm from Rodriguez et al. 2006

Wpgprfpms ⭐ 17

Random Forests population modelling scripts

[Meta R-package on CRAN] Analyse forest diversity and dynamics

R functions for project setup, data cleaning, machine learning, SuperLearner, parallelization, and targeted learning.

Forestmangr ⭐ 15

R package for forest mensuration and management

Rfutilities ⭐ 14

R package for random forests model selection, inference, evaluation and validation

Mtreering ⭐ 14

A tool for measuring tree-ring width

Indoor Positioning Via Wifi Fingerprinting ⭐ 14

Finding people's location (Building, Floor and Coordinates) at Jaume I University from WAPs signal information using classification and regression machine learning algorithms (K-NN, Gradient boosting, and Random Forest)

Material from "Random Forests and Gradient Boosting Machines in R" presented at Machine Learning Day '18

Ggaxistable ⭐ 13

ggplot2 extension to add a table to an axis.

Canonical Correlation Forest

Wetlandmapr ⭐ 12

Scripts, tools and example data for mapping wetland ecosystems using data driven R statistical methods like Random Forests and open source GIS

Randomforestforremotesensing ⭐ 12

Recursive Partitioning for Structural Equation Models

Forestoolboxrs ⭐ 12

Remote Sensing Tools for Forest Monitoring

Outforest ⭐ 11

Outlier detection based on random forest models

🔥 Forest fire history analysis in R.

Simplerf ⭐ 10

A simple implementation of random forests in plain R

Drivendata Pumpitup ⭐ 10

Set of tools to apply the probabilistic approach of Reiche et al. (2015, 2018) to combine multiple optical and/or Radar satellite time series and to detect deforestation/forest cover loss in near real-time. The package includes functions to apply the approach to both, single pixel time series and raster time series. Examples and test data are provided below.

Mlehealth ⭐ 9

Machine learning on electronic health records

Distrforest ⭐ 9

R implementation for random forests with distribution-based loss functions

Random Forest OOB Curves for any performance measure of mlr

Tidyforest ⭐ 9

A workflow of tidyverse(glm -> broom -> ggplot)

Mangrove Soil Carbon ⭐ 9

code and model output for global mangrove soil carbon project

Tutorial Machine Learning Based Survival Analysis ⭐ 9

This repository is a tutorial about survival analysis based on advanced machine learning methods including Random Forest, Gradient Boosting Tree and XGBoost. All of them are implemented in R.

Luccalculus ⭐ 8

Spatiotemporal calculus for land use change trajectories

Tradeflows ⭐ 8

Forest products trade flows database

R package for creating plots

Evidencesynthesis ⭐ 8

An R package for combining evidence from multiple sources (e.g. multiple data sites)

Cmsclassifier ⭐ 8

R package to get data from the CTA train tracker API

Extended Isolation Forests for Anomaly/Outlier Detection in R

implements multiple prediction interval methods for random forests

Detection and analysis of insect defoliators in tree rings

Data Science ⭐ 7

EDA and Machine Learning Models in R and Python (Regression, Classification, Clustering, SVM, Decision Tree, Random Forest, Time-Series Analysis, Recommender System, XGBoost)

Forest Inventory and Analysis

Spatio_temporal_causality ⭐ 7

Towards causal inference for spatio-temporal data: conflict and forest loss in Colombia

Forestdroughttool ⭐ 7

R package to analyze stand-level forest drought hazard.

Fungal Foray ⭐ 7

Working directory of of my attempt to visualize fungi-host relationships in NZ forests

Amylogram ⭐ 7

Prediction of amyloid proteins

Privateec ⭐ 7

An R package for Private Evaporative Cooling feature selection and classification with Relief-F and Random Forests

Code used for biomarker discovery using party (building conditional random forests)

Customer Churn Analysis ⭐ 6

For the last few years Betfair is losing too many customers and is finding a solution to retain its customers. Aim of this project is to build a customer churn model to predict the customers who are about to get churned so that Betfair can implement different business strategies to retain those customers before they actually leave. The tools I am using for this analysis are R-studio and Tableau. Package mlr was chosen as the modeling package. The data for the purpose of prediction was provided b

Recommendation ⭐ 6

商品推荐相关竞赛TOP5解决方案

R package for generating prediction and prediction variances from random forests.

Onlinerandomforest ⭐ 6

An R package - the implemention of Online Random Forest

Gcbm.chile.data_preprocessing ⭐ 6

This repo contains all the data preparation tools used to implement the GCBM in Chile

Gcforest_r ⭐ 6

🎨 🎨 R package for gcForest [ https://CRAN.R-project.org/package=gcForest ][ https://github.com/cran/gcForest ]

R implementation of Contextual Importance and Utility for Explainable AI

❗ This is a read-only mirror of the CRAN R package BIOMASS — Estimating Aboveground Biomass and Its U Report bugs for this package: https://github.com/u

Random Forests with a choice of splitting criteria.

Forest plot and funnel plot variants for meta-analysis

Precisetad ⭐ 5

preciseTAD: A machine learning framework for precise 3D boundary prediction at base-level resolution

Kaggle Mlsp 2014 ⭐ 5

R-Codes for RSE manuscript "Importance of sample size, data type and prediction method for remote sensing-based estimations of aboveground forest biomass"

Email Sentiment Analysis ⭐ 5

Checking the happiness quotient by analysis of emails

Computing the Singular Bayesian Information Criterion

Machine Learning ⭐ 5

Basic ML concepts in Python and R

Forestviews ⭐ 5

visualise paths through random forests:

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