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stock-plugins/aiverify.stock.shap-toolbox/algorithms/local_shap_toolbox/README.md
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| # Algorithm - local SHAP toolbox | ||
| # SHAP Toolbox | ||
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| ## Description | ||
| * local shap algorithm | ||
| This plugin explains how your features affect your overall prediction for a single row of data by using Shapley Values. | ||
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| ## License | ||
| * Licensed under Apache Software License 2.0 | ||
| ## Plugin Content | ||
| - Algorithms | ||
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| | Name | Description | | ||
| | ------------------ | ------------------------------------------------------------------------------------------------ | | ||
| | SHAP Toolbox | SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. | | ||
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| ## Developers: | ||
| * Example Author | ||
| - Widgets | ||
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| | Name | Description | | ||
| | -------------------------- | ---------------------------------------------------------------------------------------- | | ||
| | Local Explainability Chart | To display the SHAP values using a bar chart for the selection row, and display row data | | ||
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| ## Using the Plugin in AI Verify | ||
| ### Data Preparation | ||
| - Tabular dataset ([Tutorial for Preparation](https://imda-btg.github.io/aiverify/getting-started/prepare-tabular/)) | ||
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| ### Algorithm User Input(s) | ||
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| | Input Field | Description | Type | | ||
| | --------------------------- | -----------------------------------------------------------| :------: | | ||
| | Row Number | Row number of data to perform local explainability test | `int` | | ||
| | Path of the background data | Background data path | `string` | | ||
| | Size of the background | Background samples (eg. 25) | `int` | | ||
| | Size of the test dataset | Data Samples (eg. 25) | `int` | | ||
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| ### Sample use of the widgets | ||
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