Merge pull request #193844 from magrefaat/patch-87

custom text classification

Author: LJSpiller

articles/cognitive-services/language-service/custom-classification/concepts/data-formats.md

@@ -1,7 +1,7 @@
 ---
 title: Custom text classification data formats
 titleSuffix: Azure Cognitive Services
-description: Learn about the data formats accepted by custom entity extraction.
+description: Learn about the data formats accepted by custom text classification.
 services: cognitive-services
 author: aahill
 manager: nitinme
@@ -64,7 +64,7 @@ Your tags file should be in the `json` format below.
 * `documents`: An array of tagged documents.
   * `location`: The path of the file. The file has to be in root of the storage container.
   * `language`: Language of the file. Use one of the [supported culture locales](../language-support.md).
-  * `classifiers`: Array of classifier objects assigned to the file. If you're working on a single classification project, there should be one classifier per file only.
+  * `classifiers`: Array of classifier objects assigned to the file. If you're working on a single label classification project, there should be one classifier per file only.
 
 ## Next steps
 

articles/cognitive-services/language-service/custom-classification/concepts/evaluation.md

@@ -1,7 +1,7 @@
 ---
-title: Custom classification evaluation metrics
+title: Custom text classification evaluation metrics
 titleSuffix: Azure Cognitive Services
-description: Learn about evaluation metrics in custom entity extraction.
+description: Learn about evaluation metrics in custom text classification.
 services: cognitive-services
 author: aahill
 manager: nitinme
@@ -104,7 +104,7 @@ So what does it actually mean to have a high precision or a high recall for a ce
 | High | Low | The model predicts this class well, however it is with low confidence. This may be because this class is over represented in the dataset so consider balancing your data distribution. |
 | Low | Low | This class is poorly handled by the model where it is not usually predicted and when it is, it is not with high confidence. |
 
-Custom classification models are expected to experience both false negatives and false positives. You need to consider how each will affect the overall system, and carefully think through scenarios where the model will ignore correct predictions, and recognize incorrect predictions. Depending on your scenario, either *precision* or *recall* could be more suitable evaluating your model's performance.  
+Custom text classification models are expected to experience both false negatives and false positives. You need to consider how each will affect the overall system, and carefully think through scenarios where the model will ignore correct predictions, and recognize incorrect predictions. Depending on your scenario, either *precision* or *recall* could be more suitable evaluating your model's performance.  
 
 For example, if your scenario involves processing technical support tickets, predicting the wrong class could cause it to be forwarded to the wrong department/team. In this example, you should consider making your system more sensitive to false positives, and precision would be a more relevant metric for evaluation. 
 

articles/cognitive-services/language-service/custom-classification/fail-over.md

@@ -1,7 +1,7 @@
 ---
-title: Back up and recover your custom classification models
+title: Back up and recover your custom text classification models
 titleSuffix: Azure Cognitive Services
-description: Learn how to save and recover your custom classification models.
+description: Learn how to save and recover your custom text classification models.
 services: cognitive-services
 author: aahill
 manager: nitinme
@@ -17,7 +17,7 @@ ms.custom: language-service-custom-classification
 
 When you create a Language resource, you specify a region for it to be created in. From then on, your resource and all of the operations related to it take place in the specified Azure server region. It's rare, but not impossible, to encounter a network issue that hits an entire region. If your solution needs to always be available, then you should design it to either fail-over into another region. This requires two Azure Language resources in different regions and the ability to sync custom models across regions. 
 
-If your app or business depends on the use of a custom classification model, we recommend that you create a replica of your project into another supported region. So that if a regional outage occurs, you can then access your model in the other fail-over region where you replicated your project.
+If your app or business depends on the use of a custom text classification model, we recommend that you create a replica of your project into another supported region. So that if a regional outage occurs, you can then access your model in the other fail-over region where you replicated your project.
 
 Replicating a project means that you export your project metadata and assets and import them into a new project. This only makes a copy of your project settings and tagged data. You still need to [train](./how-to/train-model.md) and [deploy](how-to/call-api.md#deploy-your-model) the models to be available for use with [prediction APIs](https://aka.ms/ct-runtime-swagger).
 
@@ -132,7 +132,7 @@ Use the url from the `resultUrl` key in the body to view the exported assets fro
 
 ### Get export results
 
-Submit a **GET** request using the `{RESULT-URL}` you recieved from the previous step to view the results of the export job.
+Submit a **GET** request using the `{RESULT-URL}` you received from the previous step to view the results of the export job.
 
 #### Headers
 
@@ -330,7 +330,7 @@ Use the following header to authenticate your request.
 
 ## Deploy your model
 
-This is te step where you make your trained model available form consumption via the [runtime prediction API](https://aka.ms/ct-runtime-swagger). 
+This is the step where you make your trained model available form consumption via the [runtime prediction API](https://aka.ms/ct-runtime-swagger). 
 
 > [!TIP]
 > Use the same deployment name as your primary project for easier maintenance and minimal changes to your system to handle redirecting your traffic.

articles/cognitive-services/language-service/custom-classification/faq.md

@@ -87,9 +87,9 @@ After deploying your model, you [call the prediction API](how-to/call-api.md), u
 
 ## Data privacy and security
 
-Custom text classification is a data processor for General Data Protection Regulation (GDPR) purposes. In compliance with GDPR policies, Custom classification users have full control to view, export, or delete any user content either through the [Language Studio](https://aka.ms/languageStudio) or programmatically by using [REST APIs](https://aka.ms/ct-authoring-swagger).
+Custom text classification is a data processor for General Data Protection Regulation (GDPR) purposes. In compliance with GDPR policies, custom text classification users have full control to view, export, or delete any user content either through the [Language Studio](https://aka.ms/languageStudio) or programmatically by using [REST APIs](https://aka.ms/ct-authoring-swagger).
 
-Your data is only stored in your Azure Storage account. Custom classification only has access to read from it during training.
+Your data is only stored in your Azure Storage account. Custom text classification only has access to read from it during training.
 
 ## How to clone my project?
 

articles/cognitive-services/language-service/custom-classification/how-to/call-api.md

@@ -1,5 +1,5 @@
 ---
-title: How to submit custom classification tasks
+title: How to submit custom text classification tasks
 titleSuffix: Azure Cognitive Services
 description: Learn about sending a request for custom text classification.
 services: cognitive-services
@@ -19,7 +19,7 @@ After you're satisfied with your model, and made any necessary improvements, you
 
 ## Prerequisites
 
-* [A custom classification project](create-project.md) with a configured Azure blob storage account, 
+* [A custom text classification project](create-project.md) with a configured Azure blob storage account, 
 * Text data that has [been uploaded](create-project.md#prepare-training-data) to your storage account.
 * [Tagged data](tag-data.md) and successfully [trained model](train-model.md)
 * Reviewed the [model evaluation details](view-model-evaluation.md) to determine how your model is performing.
@@ -86,7 +86,7 @@ First you will need to get your resource key and endpoint
 
     :::image type="content" source="../media/get-endpoint-azure.png" alt-text="Get the Azure endpoint" lightbox="../media/get-endpoint-azure.png":::
 
-### Submit text classification task
+### Submit a custom text classification task
 
 1. Start constructing a POST request by updating the following URL with your endpoint.
 
@@ -97,7 +97,7 @@ First you will need to get your resource key and endpoint
 3. In the JSON body of your request, you will specify The documents you're inputting for analysis, and the parameters for the custom entity recognition task. `project-name` is case-sensitive.
 
     > [!tip]
-    > See the [quickstart article](../quickstart.md?pivots=rest-api#submit-text-classification-task) and [reference documentation](https://westus2.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v3-2-Preview-2/operations/Analyze) for more information about the JSON syntax.
+    > See the [quickstart article](../quickstart.md?pivots=rest-api#submit-a-custom-text-classification-task) and [reference documentation](https://westus2.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v3-2-Preview-2/operations/Analyze) for more information about the JSON syntax.
     
     ```json
     {
@@ -166,7 +166,7 @@ First you will need to get your resource key and endpoint
     * [JavaScript](https://github.com/Azure/azure-sdk-for-js/blob/main/sdk/textanalytics/ai-text-analytics/samples/v5/javascript/customText.js)
     * [Python](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/textanalytics/azure-ai-textanalytics/samples/sample_single_category_classify.py)
 
-    Multiple label classification:
+    Multi label classification:
     * [C#](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/textanalytics/Azure.AI.TextAnalytics/samples/Sample11_MultiCategoryClassify.md)
     * [Java](https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/lro/ClassifyDocumentMultiCategory.java)
     * [JavaScript](https://github.com/Azure/azure-sdk-for-js/blob/main/sdk/textanalytics/ai-text-analytics/samples/v5/javascript/customText.js)

articles/cognitive-services/language-service/custom-classification/how-to/create-project.md

@@ -1,7 +1,7 @@
 ---
 title: How to create custom text classification projects
 titleSuffix: Azure Cognitive Services
-description: Learn about the steps for using Azure resources with custom classification.
+description: Learn about the steps for using Azure resources with custom text classification.
 services: cognitive-services
 author: aahill
 manager: nitinme
@@ -28,7 +28,7 @@ Before you start using custom text classification, you will need several things:
 
 ## Azure resources
 
-Before you start using custom classification, you will need an Azure Language resource. We recommend following the steps below for creating your resource in the Azure portal. Creating a resource in the Azure portal lets you create an Azure storage account at the same time, with all of the required permissions pre-configured. You can also read further in the article to learn how to use a pre-existing resource, and configure it to work with custom text classification.
+Before you start using custom text classification, you will need an Azure Language resource. We recommend following the steps below for creating your resource in the Azure portal. Creating a resource in the Azure portal lets you create an Azure storage account at the same time, with all of the required permissions pre-configured. You can also read further in the article to learn how to use a pre-existing resource, and configure it to work with custom text classification.
 
 You also will need an Azure storage account where you will upload your `.txt` files that will be used to train a model to classify text.
 
@@ -45,12 +45,12 @@ You also will need an Azure storage account where you will upload your `.txt` fi
 If it's your first time logging in, you'll see a window in [Language Studio](https://aka.ms/languageStudio) that will let you choose a language resource or create a new one. You can also create a resource by clicking the settings icon in the top-right corner, selecting **Resources**, then clicking **Create a new resource**.
 
 > [!IMPORTANT]
-> * To use Custom Text Classification, you'll need a Language resource in **West US 2** or **West Europe** with the Standard (**S**) pricing tier.
+> * To use custom text classification, you'll need a Language resource in **West US 2** or **West Europe** with the Standard (**S**) pricing tier.
 > * Be sure to to select **Managed Identity** when you create a resource. 
 
 :::image type="content" source="../../media/create-new-resource-small.png" alt-text="A screenshot showing the resource creation screen in Language Studio." lightbox="../../media/create-new-resource.png":::
 
-To use custom classification, you'll need to [create an Azure storage account](../../../../storage/common/storage-account-create.md) if you don't have one already. 
+To use custom text classification, you'll need to [create an Azure storage account](../../../../storage/common/storage-account-create.md) if you don't have one already. 
 
 Next you'll need to assign the [correct roles](#roles-for-your-storage-account) for the storage account to connect it to your Language resource. 
 
@@ -95,7 +95,7 @@ You can use an existing Language resource to get started with custom text classi
 |Pricing tier     | Make sure your existing resource is in the Standard (**S**) pricing tier. Only this pricing tier is supported. If your resource doesn't use this pricing  tier, you will need to create a new resource.        |
 |Managed identity     | Make sure that the resource-managed identity setting is enabled. Otherwise, read the next section. |
 
-To use custom classification, you'll need to [create an Azure storage account](../../../../storage/common/storage-account-create.md) if you don't have one already. 
+To use custom text classification, you'll need to [create an Azure storage account](../../../../storage/common/storage-account-create.md) if you don't have one already. 
 
 Next you'll need to assign the [correct roles](#roles-for-your-storage-account) for the storage account to connect it to your Language resource. 
 

articles/cognitive-services/language-service/custom-classification/how-to/design-schema.md

@@ -1,7 +1,7 @@
 ---
 title: How to prepare data and define a schema
 titleSuffix: Azure Cognitive Services
-description: Learn about data selection, preparation, and creating a schema for custom classification projects.
+description: Learn about data selection, preparation, and creating a schema for custom text classification projects.
 services: cognitive-services
 author: aahill
 manager: nitinme
@@ -15,7 +15,7 @@ ms.custom: language-service-custom-classification, ignite-fall-2021
 
 # How to prepare data and define a schema
 
-In order to create a custom classification model, you will need quality data to train it. This article covers how you should approach selecting and preparing your data, along with defining a schema. A schema defines the classes that you need your model to classify your text into at runtime, and is the first step of [developing a custom classification application](../overview.md#project-development-lifecycle).
+In order to create a custom text classification model, you will need quality data to train it. This article covers how you should approach selecting and preparing your data, along with defining a schema. A schema defines the classes that you need your model to classify your text into at runtime, and is the first step of [developing a custom classification application](../overview.md#project-development-lifecycle).
 
 
 ## Data selection
@@ -62,4 +62,4 @@ The schema defines the classes that you need your model to classify your text in
 
 ## Next steps
 
-If you haven't already, create a custom classification project. If it's your first time using custom classification, consider following the [quickstart](../quickstart.md) to create an example project. You can also see the [project requirements](../how-to/create-project.md) for more details on what you need to create a project.
+If you haven't already, create a custom text classification project. If it's your first time using custom text classification, consider following the [quickstart](../quickstart.md) to create an example project. You can also see the [project requirements](../how-to/create-project.md) for more details on what you need to create a project.

articles/cognitive-services/language-service/custom-classification/how-to/improve-model.md

@@ -21,7 +21,7 @@ After you've trained your model you reviewed its evaluation details, you can dec
 
 To optionally improve a model, you will need to have:
 
-* [A custom classification project](create-project.md) with a configured Azure blob storage account, 
+* [A custom text classification project](create-project.md) with a configured Azure blob storage account, 
 * Text data that has [been uploaded](create-project.md#prepare-training-data) to your storage account.
 * [Tagged data](tag-data.md) to successfully [train a model](train-model.md)
 * Reviewed the [model evaluation details](view-model-evaluation.md) to determine how your model is performing.

articles/cognitive-services/language-service/custom-classification/how-to/tag-data.md

@@ -61,9 +61,9 @@ Use the following steps to tag your data
 
       :::image type="content" source="../media/tag-single.png" alt-text="A screenshot showing the single label classification menu" lightbox="../media/tag-single.png":::
 
-    * **Multiple label classification**: your file can be tagged with multiple classes, you can do so by checking all applicable check boxes next to the classes you want to tag this file with.
+    * **Multi label classification**: your file can be tagged with multiple classes, you can do so by checking all applicable check boxes next to the classes you want to tag this file with.
 
-      :::image type="content" source="../media/tag-multi.png" alt-text="A screenshot showing the multiple label classification menu" lightbox="../media/tag-multi.png":::
+      :::image type="content" source="../media/tag-multi.png" alt-text="A screenshot showing the multi label classification menu" lightbox="../media/tag-multi.png":::
 
 While tagging, your changes will be synced periodically, if they have not been saved yet you will find a warning at the top of your page. If you want to save manually, click on Save tags button at the top of the page.
 

articles/cognitive-services/language-service/custom-classification/how-to/train-model.md

@@ -1,5 +1,5 @@
 ---
-title: How to train your custom classification model - Azure Cognitive Services
+title: How to train your custom text classification model - Azure Cognitive Services
 titleSuffix: Azure Cognitive Services
 description: Learn about how to train your model for custom text classification.
 services: cognitive-services
@@ -13,7 +13,7 @@ ms.author: aahi
 ms.custom: language-service-custom-classification, ignite-fall-2021
 ---
 
-# How to train a text classification model
+# How to train a custom text classification model
 
 
 Training is the process where the model learns from your [tagged data](tag-data.md). After training is completed, you will be able to [use the model evaluation metrics](../how-to/view-model-evaluation.md) to determine if you need to [improve your model](../how-to/improve-model.md).
@@ -30,7 +30,7 @@ See the [application development lifecycle](../overview.md#project-development-l
 
 ## Data split
 
-Before starting the training process, files in your dataset are divided into three groups at random:
+Before you start the training process, files in your dataset are divided into three groups at random:
 
 * The **training set** contains 80% of the files in your dataset. It is the main set that is used to train the model.