R package that makes basic data exploration radically simple (interactive data exploration, reproducible data science)
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Updated
Dec 6, 2024 - R
R package that makes basic data exploration radically simple (interactive data exploration, reproducible data science)
Heatmap-integrated Decision Tree Visualizations
Misc Statistics and Machine Learning codes in R
Top 5th percentile solution to the Kaggle knowledge problem - Bike Sharing Demand
This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.
🌲 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.
This repository should help people that would like to code in R and work with the National Health and Nutrition Examination Survey (NHANES). Some topics corved are SQL , logistic regression.... etc
Material from "Random Forests and Gradient Boosting Machines in R" presented at Machine Learning Day '18
tidytrees: a package for a tidy representation of decision trees.
We used different machine learning approaches to build models for detecting and visualizing important prognostic indicators of breast cancer survival rate. This repository contains R source codes for 5 steps which are, model evaluation, Random Forest further modelling, variable importance, decision tree and survival analysis. These can be a pipe…
Predict respiratory patient mortality in ICU units using the MIMIC III database
Analyze NASDAQ100 stock data. Used ARIMA + GARCH model and machine learning techniques Naive Bayes and Decision tree to determine if we go long or short for a given stock on a particular day
R codes for common Machine Learning Algorithms
🌳 🎯 Cross Validated Decision Trees with Targeted Maximum Likelihood Estimation
The feature of interest is whether or not a customer buys a caravan insurance, based on socio-demographic factors and ownership of other insurance policies; and to build profile of a typical customer.
Classic Machine Learning in R
Generate Decision Tree With Bank Marketing Dataset
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