R mlr is described as 'mlr provides this so that you can focus on your experiments! The framework provides supervised methods like classification, regression and survival analysis along with their corresponding evaluation and optimization methods, as well as unsupervised methods like clustering'. There are six alternatives to R mlr for a variety of platforms, including Windows, Linux, Mac, R (programming language) and Self-Hosted solutions. The best alternative is datarobot. It's not free, so if you're looking for a free alternative, you could try python auto-sklearn or R MLstudio. Other great apps like R mlr are ML.NET (Free, Open Source), H2O.ai (Free, Open Source) and R Caret (Free Personal, Open Source).
The ML Studio is interactive for EDA, statistical modeling and machine learning applications. Based on Shiny, with Plotly interactive data visualization, DT HTML tables and H2O machine learning and deep. data science pipeline workflow.
H2O is an open source, in-memory, distributed, fast, and scalable machine learning and predictive analytics platform that allows you to build machine learning models on big data and provides easy productionalization of those models in enterprise env.
The caret package (short for _C_lassification _A_nd _RE_gression _T_raining) is a set of functions that attempt to streamline the process for creating predictive models. data splitting pre-processing feature selection model tuning using resampling.