Knowledge Studio 2022.0 introduces several important improvements that make the software easier than ever to use and deploy. Docker is no longer required to support any Knowledge Studio functionality, which makes deployments easier, eliminates certain compliance issues, and saves money. The software now offers a new decision tree tab and we have made enhancements to the SHAP tab and the decision tree tab provides a visual and easy-to-understand way to explain black box models. A single standardized scoring node is now applicable to all native models, ARIMA Forecasting, Keras Deep Learning, Novelty & Outlier Detector, GLM, and XGB models; this improves usability, simplifies the process of building workflows, and removes clutter from the Action function palette. Users can also now specify custom Python and R execution environments in the Python and R Code nodes, which allows them to use any version of Python or R with Knowledge Studio.
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