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This analysis is essential in the iterative process of model design and feature engineering, and is usually performed manually. \n\nThe Model Error Analysis plugin provides the user with automatic tools to break down the model’s errors into meaningful groups, easier to analyze, and to highlight the most frequent type of errors, as well as the problematic characteristics correlated with the errors. \n\n\n## Scope of the plugin\nThis plugin offers a set of different DSS components to analyse the error of a deployed model:\n* Model view: visualise the Error Tree and analyse the subgroups that conatain the most errors. \n* Template notebook: tutorial to use the python library and its api.\n\n## Installation and requirements\n\nPlease see our [official plugin page](https://www.dataiku.com/product/plugins/model-error-analysis/) for installation.\n\n## Issues\n\nYou can log feature requests or issues on our [dedicated Github repository](https://github.com/dataiku/dss-plugin-model-error-analysis/issues).\n\n# License\n\nThe Model Error Analysis plugin is:\n\n   Copyright (c) 2021 Dataiku\n   Licensed under the [Apache License](LICENSE).\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdataiku%2Fdss-plugin-model-error-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdataiku%2Fdss-plugin-model-error-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdataiku%2Fdss-plugin-model-error-analysis/lists"}