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Fixes dead links in the `Integrating ML models` document (#6149) 

Signed-off-by: linghengqian <linghengqian@outlook.com>
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Ling Hengqian 2024-01-16 04:34:34 +08:00 committed by GitHub
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_ml-commons-plugin/integrating-ml-models.md
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@ -50,7 +50,7 @@ You can use an ML model in one of the following ways:
### Making predictions ### Making predictions
[Models trained]({{site.url}}{{site.baseurl}}//ml-commons-plugin/api/train-predict/train/) through the ML Commons plugin support model-based algorithms, such as k-means. After you've trained a model to your precision requirements, use the model to [make predictions]({{site.url}}{{site.baseurl}}/ml-commons-plugin/api/train-predict/predict/). [Models trained]({{site.url}}{{site.baseurl}}/ml-commons-plugin/api/train-predict/train/) through the ML Commons plugin support model-based algorithms, such as k-means. After you've trained a model to your precision requirements, use the model to [make predictions]({{site.url}}{{site.baseurl}}/ml-commons-plugin/api/train-predict/predict/).
If you don't want to use a model, you can use the [Train and Predict API]({{site.url}}{{site.baseurl}}/ml-commons-plugin/api/train-predict/train-and-predict/) to test your model without having to evaluate the model's performance. If you don't want to use a model, you can use the [Train and Predict API]({{site.url}}{{site.baseurl}}/ml-commons-plugin/api/train-predict/train-and-predict/) to test your model without having to evaluate the model's performance.