How does R programming support machine learning and predictive modelling in research applications? Can you highlight some popular R packages and algorithms that researchers can use for building and evaluating predictive models?
Hello Mr. Dinesh Kumar,
In my opinion the most complete modelling library in R would be caret, it supports lots of different models (machine learning included) for regression and classification. I am sure that you will enjoy consulting its extensive reference manual.
However, if you would like to know other libraries focused on specific models, I recommend that you consult the CRAN Task Views: https://cran.r-project.org/web/views/MachineLearning.html
Regards,
R is more specially designed for statistical modelling, similar to MATLAB for mathematical modelling and scientific computing at first hand and then for other computing applications from everywhere.
To perform predictions, I use gradient boosting models, thus, i use the package gbm. It depends on the model that you want to use there are also for example rf for random forest xgboost for Extreme gradient boosting. Caret is a good package but for Linear or Logistic Regression that are more inference models.
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