Check out the Statistics Globe Hub: statisticsglobe.com/hub The Statistics Globe Hub is an ongoing learning program that helps you stay up to date with statistics, data science, AI, and programming using R and Python. #randomforest #featureselection #machinelearning #datascience #rstats #statisticsglobehub

ヴァルハラで静かに眠る「巨人の遺物」。ローマ廃墟の哀愁にRandom Forestの美しいアンビエントを重ねました。 sg-walker.com/assassins_cree… #アサクリ #ポストロック #RandomForest #ゲーム考察 #北欧神話

🌳 MÉTODOS BASADOS EN ÁRBOLES En 1 minuto te explico cómo funcionan los modelos más intuitivos del machine learning Perfecto si buscas modelos potentes sin perder interpretabilidad. 📊 #ÁrbolesDeDecisión #RandomForest #Boosting #MachineLearning #Estadística #CienciaDeDatosAW

If you are interested I recommened watching this video: StatQuest: Random Forests Part 1 - Building, Using and Evaluating #PolymathJourney #RandomForest #MachineLearning #DataScience #ArtificialIntelligence #Coding #AlgorithmExplained #TechEducation #BigData

📢 #highlycited paper 📚 Hazard Prediction of Water Inrush in #Water_RichTunnels Based on #RandomForest Algorithm 🔗 mdpi.com/2076-3417/14/2… 👨‍🔬 by Nian Zhang et al. 🏫 Taiyuan University of Technology/Shanxi Provincial Key Laboratory of Civil Engineering Disaster Prevention and Control/Ministry of Transport #datapreprocessing #machinelearning

👋👋 GNSS-IR #SoilMoisture Retrieval Using Multi-Satellite #Data Fusion Based on #RandomForest ✍️ Yao Jiang et al. 🔗 brnw.ch/21x0OvUX9N

Random Forest: Combining many decision trees for better predictions. Like asking multiple experts and taking a vote. Collective intelligence. @TopicTrick #TopicTrick #RandomForest #AI #Ensemble

6/6 RF won't give you a counterfactual. But it tells you where to look — which variables matter, which targeting criteria hold up, where your theory of change may need revisiting. A sharp complement to any causal model. #evaluation #MEL #randomforest #datascience #publichealth

5/6 What this tells us: Climate stress is nearly as predictive as age — it's a core driver, not in the background. Household size matters more than which county you're in. That reshapes how you think about targeting. #evaluation #randomforest #datascience #KRABodyCam

3/6 Why should evaluators care? Because context matters as much as effect size. RF ranks variables by predictive power — no linearity needed, no pre-specified functional form, no collapse under correlated predictors. #evaluation #randomforest #datascience #KRABodyCam

2/6 It builds hundreds of decision trees, each on a random data subset. Then aggregates: majority vote for classification, average for regression. More stable than any single tree. Far less prone to overfitting. #evaluation #randomforest #datascience #KRABodyCam

1/6 What's actually causing child wasting in your program areas? "We think it's drought" is not an answer. There's a tool (Random Forest) that ranks the drivers for you. 🧵 #evaluation #randomforest #datascience #KRABodyCam3