iml: An R package for Interpretable Machine Learning
نویسندگان
چکیده
منابع مشابه
Making machine learning models interpretable
Data of different levels of complexity and of ever growing diversity of characteristics are the raw materials that machine learning practitioners try to model using their wide palette of methods and tools. The obtained models are meant to be a synthetic representation of the available, observed data that captures some of their intrinsic regularities or patterns. Therefore, the use of machine le...
متن کاملexprso: an R-package for the rapid implementation of machine
Machine learning plays a major role in many scientific investigations. However, non-expert programmers may struggle to implement the elaborate pipelines necessary to build highly accurate and generalizable models. We introduce here a new R package, exprso, as an intuitive machine learning suite designed specifically for non-expert programmers. Built primarily for the classification of high-dime...
متن کاملexprso: an R-package for the rapid implementation of machine
Machine learning plays a major role in many scientific investigations. However, non-expert programmers may struggle to implement the elaborate pipelines necessary to build highly accurate and generalizable models. We introduce here a new R package, exprso, as an intuitive machine learning suite designed specifically for non-expert programmers. Built primarily for the classification of high-dime...
متن کاملInteractive Machine Learning (iML): a challenge for Game-based approaches
The goal of the ML-community is to design and develop algorithms which can learn from data and improve with experience over time. However, the application of such automatic machine learning (aML) approaches in the complex biomedical domain seems elusive in the near future, and a good example are Gaussian processes, where aML (e.g. standard kernel machines) struggle on function extrapolation pro...
متن کاملexprso: an R-package for the rapid implementation of machine learning algorithms
Machine learning plays a major role in many scientific investigations. However, non-expert programmers may struggle to implement the elaborate pipelines necessary to build highly accurate and generalizable models. We introduce exprso, a new R package that is an intuitive machine learning suite designed specifically for non-expert programmers. Built initially for the classification of high-dimen...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Open Source Software
سال: 2018
ISSN: 2475-9066
DOI: 10.21105/joss.00786