What's new and changed in Watson OpenScale
Watson OpenScale updates can include new features, bug fixes, and security updates. Releases are listed in reverse chronological order so that the latest release is at the beginning of the topic.
You can see a list of the new features for the platform and all of the services at What's new in IBM Cloud Pak for Data.
Installing or upgrading Watson OpenScale
Ready to install or upgrade Watson OpenScale?
- To install Watson OpenScale along with the other Cloud Pak for Data services, see Installing Cloud Pak for Data.
- To upgrade Watson OpenScale along with the other Cloud Pak for Data services, see Upgrading Cloud Pak for Data.
- To install or upgrade Watson
OpenScale independently,
see Watson
OpenScale.Remember: All of the Cloud Pak for Data components associated with an instance of Cloud Pak for Data must be installed at the same version.
Cloud Pak for Data Version 5.0.3
A new version of Watson OpenScale was released in September 2024 with Cloud Pak for Data 5.0.3.
Operand version: 5.0.3
This release includes the following changes:
- Updates
- The following updates were introduced in this release:
- New quality evaluation metrics for regression models
- You can now configure the following new quality metrics for regression models:
- Mean absolute percentage error
- Symmetric mean absolute percentage error
- Pearson correlation coefficient
- Spearman correlation coefficient
For more information, see Quality evaluations.
Cloud Pak for Data Version 5.0.1
A new version of Watson OpenScale was released in July 2024 with Cloud Pak for Data 5.0.1.
Operand version: 5.0.1
This release includes the following changes:
- Security issues fixed in this release
- The following security issues were fixed in this release:
Cloud Pak for Data Version 5.0.0
A new version of Watson OpenScale was released in June 2024 with Cloud Pak for Data 5.0.0.
Operand version: 5.0.0
This release includes the following changes:
- New features
-
This release of Watson OpenScale includes the following features:
- New quality metric for binary classification models
- You can now configure the gini coefficient metric when you run quality evaluations for binary
classification models. The gini coefficient metric measures the inequality of model distributions.
For more information, see Quality evaluations.
- Updates
- The following updates were introduced in this release:
When you enable drift v2 evaluations, the output drift metric can now measure the performance of unstructured text and unstructured image models.
- Security issues fixed in this release
- The following security issues were fixed in this release:
CVE-2024-1135, CVE-2024-3568, CVE-2024-3651, CVE-2023-45288, CVE-2022-40897, CVE-2024-23944, CVE-2024-29133, CVE-2024-29131, CVE-2024-24786, CVE-2024-34062, CVE-2024-34069, CVE-2024-34064, CVE-2024-28863, CVE-2024-27983
CVE-2023-25613, CVE-2023-43787, CVE-2023-3138, CVE-2023-25193, CVE-2023-47627, CVE-2023-45288
CVE-2022-40897, CVE-2022-40897
CVE-2020-11022, CVE-2020-11023, CVE-2020-23064, CVE-2020-7656
CVE-2019-11358
CVE-2015-9251
CVE-2012-6708
CVE-2011-4969