Summary
Overview
The Model Evaluation Python toolkit for Spotfire utilizes the Scikit learn Python package, which provides a set of evaluation metrics to monitor and measure the performance of your machine learning model during training and testing of your regression and classification models. These metrics tell you if you're making progress with respect to model building part of your machine learning pipeline.
Installing the data function
Follow the online guide available here to register a data function in Spotfire.
Configuring the data function
Each data function may require inputs from the Spotfire analysis and will return outputs to the Spotfire analysis. For each data function, these need to be configured once the data function is registered. To learn about how to configure data functions in Spotfire please view this video:
For more information on Spotfire visit the Spotfire Training Page.
Data function library
There exists a large number of data functions covering various features. Feel free to review what is available on the Data Function Library.
Initial Release (version 1.0.0)
Published: April 2022
Initial release includes:
- Set of Python data functions for model evaluation tasks
- Dxp with example usage
- Documentation
- License information