Merge pull request #581 from opensearch-project/Fix#560
Fixed issue #560
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# Contributing Guidelines
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Thank you for your interest in contributing to our project. Whether it's a bug report, new feature, correction, or additional
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Thank you for your interest in contributing to the OpenSource documentation! Whether it's a bug report, new feature, correction, or additional
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documentation, we greatly value feedback and contributions from our community.
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Please read through this document before submitting any issues or pull requests to ensure we have all the necessary
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@ -9,7 +9,7 @@ information to effectively respond to your bug report or contribution.
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## Reporting Bugs/Feature Requests
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We welcome you to use the GitHub issue tracker to report bugs or suggest features.
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Use the GitHub issue tracker to report bugs or suggest features.
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When filing an issue, please check existing open, or recently closed, issues to make sure somebody else hasn't already
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reported the issue. Please try to include as much information as you can. Details like these are incredibly useful:
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@ -20,7 +20,7 @@ The Machine Learning (ML) commons API lets you train ML algorithms synchronously
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In order to train tasks through the API, three inputs are required.
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- Algorithm name: Must be one of a [FunctionaName](https://github.com/opensearch-project/ml-commons/blob/1.3/common/src/main/java/org/opensearch/ml/common/parameter/FunctionName.java). This determines what algorithm the ML Engine runs. To add a new function, see [How To Add a New Function](https://github.com/opensearch-project/ml-commons/blob/main/docs/how-to-add-new-function.md).
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- Algorithm name: Must be one of a [FunctionName](https://github.com/opensearch-project/ml-commons/blob/1.3/common/src/main/java/org/opensearch/ml/common/parameter/FunctionName.java). This determines what algorithm the ML Engine runs. To add a new function, see [How To Add a New Function](https://github.com/opensearch-project/ml-commons/blob/main/docs/how-to-add-new-function.md).
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- Model hyper parameters: Adjust these parameters to make the model train better.
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- Input data: The data input that trains the ML model, or applies the ML models to predictions. You can input data in two ways, query against your index or use data frame.
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