The R Interface

R has evolved continuously, establishing itself as the standard software platform, particularly notable for its integration of cutting-edge statistical functionalities, especially in the domains of Artificial Intelligence and Machine Learning.

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R integration with Cornerstone

By connecting Cornerstone with R, we enable access to R’s powerful state-of-the-art functionalities to pre-process, analyze and visualize data within the dynamic interactive and user-friendly Workmap structure of Cornerstone.

Undoubtedly, the capabilities of R can significantly augment the core functions of Cornerstone. Therefore, camLine developed the free extension CornerstoneR with various statistical functionalities that you can use without any programming knowledge in R.

CornerstoneR version 3.4: Functionalities

Features Highlight

CornerstoneR extension features many functionalities for statistical modeling and predicting, such as:

Neural Networks
Gaussian Process Regression
Decision Trees
Random Forests
Function Fitting

The Model Predict function enables you to predict response values for unseen data. Especially in Machine Learning, it’s common practice to split the data into training and testing data, using the test dataset to validate the model.

The new Neural Networks feature in CornerstoneR 3.4 expands the machine learning capabilities of the package by enabling powerful nonlinear predictive modeling.

In addition, Version 3.4 enhances Time Series Models with coefficient tables and confidence level script variables and improves the output options of several machine learning methods.

camLine_Cheatsheet_CornerstoneR_202510_Internal

Enhanced Data Analysis with CornerstoneR 3.4

In addition, camLine offers you quick solutions for your data analysis problems, as your CornerstoneR team is continuously and fast developing the R interface and its extension. However, users with R knowledge can also write their own R script in Cornerstone or load their R scripts and packages into Cornerstone.

For the new version CornerstoneR 3.4, Cornerstone and R are required.

Download the CornerstoneR 3.4.0 Installer Package Download CornerstoneR Cheat Sheet

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