Local Interpretable Model-Agnostic Explanations (R port of original Python package)
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Updated
Aug 19, 2022 - R
Local Interpretable Model-Agnostic Explanations (R port of original Python package)
Developer Version of the R package CAST: Caret Applications for Spatio-Temporal models
Conformal Time Series Forecasting Using State of Art Machine Learning Algorithms
A Minimalistic Framework for Creating, Managing and Training Multiple Caret Models
Applied Predictive Modeling with caret
Exercises From Book "Applied Predictive Modeling" by "Kuhn and Johnson (2013)"
Large-scale digital mapping of soil organic carbon content by using machine learning algorithms
R exercises (2016)
Create APIs for the deployment of R models with minimal code
Web application using machine learning algorithms to predict whether an NBA team will cover the spread.
We use machine learning techniques for identification of the best cognitive markers for cocaine dependence.
Support Vector Machine
SuperLearner R package: prediction model ensembling method
Entry for the Titanic: Machine Learning from Disaster competition on Kaggle.
Comparing different data preprocessing methods to predict soil organic carbon content on soil spectra features
The code evaluates data using various machine learning algorithms using the Caret package in R
Caret R Models Deployment using SQL databases
Exploratory data analysis, missing value imputation and linear models on carnicoma data
For the Report Exercise of AGDS 2.
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