AWS frauddetector documentation change
Summary
Corrected API documentation URLs by adding an extra slash in the path
Security assessment
The changes only fix URL formatting by adding an extra slash in API documentation links. There is no mention of security vulnerabilities, mitigations, or security feature enhancements. The modifications are purely documentation link corrections without security implications.
Diff
diff --git a/frauddetector/latest/ug/getting-started-python.md b/frauddetector/latest/ug/getting-started-python.md index dc66c1d22..1acdfe59d 100644 --- a//frauddetector/latest/ug/getting-started-python.md +++ b//frauddetector/latest/ug/getting-started-python.md @@ -55 +55 @@ A variable is a data element from your dataset that you want to use to create ev -In the following example,the [CreateVariable](https://docs.aws.amazon.com/frauddetector/latest/api/API_CreateVariable.html) API is used to create two variables. The variables are `email_address` and `ip_address`. Assign them to the corresponding variable types: `EMAIL_ADDRESS` and `IP_ADDRESS`. These variables are part of the example dataset you uploaded. When you specify the variable type, Amazon Fraud Detector interprets the variable during model training and when getting predictions. Only variables with an associated variable type can be used for model training. +In the following example,the [CreateVariable](https://docs.aws.amazon.com//frauddetector/latest/api/API_CreateVariable.html) API is used to create two variables. The variables are `email_address` and `ip_address`. Assign them to the corresponding variable types: `EMAIL_ADDRESS` and `IP_ADDRESS`. These variables are part of the example dataset you uploaded. When you specify the variable type, Amazon Fraud Detector interprets the variable during model training and when getting predictions. Only variables with an associated variable type can be used for model training. @@ -84 +84 @@ An entity represents who is performing the event and an entity type classifies t -In the following example, [PutEntityType](https://docs.aws.amazon.com/frauddetector/latest/api/API_PutEntityType.html) API is used to create a `sample_customer` entity type. +In the following example, [PutEntityType](https://docs.aws.amazon.com//frauddetector/latest/api/API_PutEntityType.html) API is used to create a `sample_customer` entity type. @@ -101 +101 @@ A label classifies an event as fraudulent or legitimate and is used to train the -In the following example, the [Putlabel](https://docs.aws.amazon.com/frauddetector/latest/api/API_PutLabel.html) API is used to create two labels, `fraud` and `legit`. +In the following example, the [Putlabel](https://docs.aws.amazon.com//frauddetector/latest/api/API_PutLabel.html) API is used to create two labels, `fraud` and `legit`. @@ -120 +120 @@ With Amazon Fraud Detector, you build models that evaluate risks and generate fr -In the following example, the [PutEventType](https://docs.aws.amazon.com/frauddetector/latest/api/API_PutEventType.html) API is used to create an event type `sample_registration`. You define the event type by specifying the variables (`email_address`,`ip_address`), entity type (`sample_customer`), and labels (`fraud`, `legit`) that you created in the previous step. +In the following example, the [PutEventType](https://docs.aws.amazon.com//frauddetector/latest/api/API_PutEventType.html) API is used to create an event type `sample_registration`. You define the event type by specifying the variables (`email_address`,`ip_address`), entity type (`sample_customer`), and labels (`fraud`, `legit`) that you created in the previous step. @@ -141 +141 @@ For more information about different model types that Amazon Fraud Detector supp -In the following example, the [CreateModel](https://docs.aws.amazon.com/frauddetector/latest/api/API_CreateModel.html) API is used to create a model. +In the following example, the [CreateModel](https://docs.aws.amazon.com//frauddetector/latest/api/API_CreateModel.html) API is used to create a model. @@ -155 +155 @@ In the following example, the [CreateModel](https://docs.aws.amazon.com/frauddet -In the following example, the [CreateModelVersion](https://docs.aws.amazon.com/frauddetector/latest/api/API_CreateModelVersion.html) API is used to train the model. Specify `'EXTERNAL_EVENTS'` for the `trainingDataSource` and the Amazon S3 location where you stored your example dataset and the _RoleArn_ of the Amazon S3 bucket for `externalEventsDetail`. For `trainingDataSchema` parameter, specify how Amazon Fraud Detector interprets the example data. More specifically, specify which variables to include and how to classify the event labels. +In the following example, the [CreateModelVersion](https://docs.aws.amazon.com//frauddetector/latest/api/API_CreateModelVersion.html) API is used to train the model. Specify `'EXTERNAL_EVENTS'` for the `trainingDataSource` and the Amazon S3 location where you stored your example dataset and the _RoleArn_ of the Amazon S3 bucket for `externalEventsDetail`. For `trainingDataSchema` parameter, specify how Amazon Fraud Detector interprets the example data. More specifically, specify which variables to include and how to classify the event labels. @@ -187 +187 @@ An important step in using Amazon Fraud Detector is to assess the accuracy of yo -Use the [DescribeModelVersions](https://docs.aws.amazon.com/frauddetector/latest/api/API_DescribeModelVersions.html) API to review model performance. Look at the **Model performance** overall score and all other metrics generated by Amazon Fraud Detector for this model. +Use the [DescribeModelVersions](https://docs.aws.amazon.com//frauddetector/latest/api/API_DescribeModelVersions.html) API to review model performance. Look at the **Model performance** overall score and all other metrics generated by Amazon Fraud Detector for this model. @@ -195 +195 @@ You can expect all your trained Amazon Fraud Detector models to have real-world -After you reviewed the performance metrics of your trained model, deploy the model and make it available to Amazon Fraud Detector to generate fraud predictions. To deploy the trained model, use the [UpdateModelVersionStatus](https://docs.aws.amazon.com/frauddetector/latest/api/API_UpdateModelVersionStatus.html) API. In the following example, it's used to update the model version status to ACTIVE. +After you reviewed the performance metrics of your trained model, deploy the model and make it available to Amazon Fraud Detector to generate fraud predictions. To deploy the trained model, use the [UpdateModelVersionStatus](https://docs.aws.amazon.com//frauddetector/latest/api/API_UpdateModelVersionStatus.html) API. In the following example, it's used to update the model version status to ACTIVE. @@ -215 +215 @@ Use the following example codes to create detector, rules, outcome, and to publi -In the following example, the [PutDetector](https://docs.aws.amazon.com/frauddetector/latest/api/API_PutDetector.html) API is used to create a `sample_detector` detector for `sample_registration` event type. +In the following example, the [PutDetector](https://docs.aws.amazon.com//frauddetector/latest/api/API_PutDetector.html) API is used to create a `sample_detector` detector for `sample_registration` event type. @@ -229 +229 @@ In the following example, the [PutDetector](https://docs.aws.amazon.com/frauddet -Outcomes are created for each possible fraud prediction result. In the following example, the [PutOutcome](https://docs.aws.amazon.com/frauddetector/latest/api/API_PutOutcome.html) API is used to create three outcomes - `verify_customer`, `review`, and `approve`. These outcomes are later assigned to rules. +Outcomes are created for each possible fraud prediction result. In the following example, the [PutOutcome](https://docs.aws.amazon.com//frauddetector/latest/api/API_PutOutcome.html) API is used to create three outcomes - `verify_customer`, `review`, and `approve`. These outcomes are later assigned to rules. @@ -256 +256 @@ Rule consists of one or more variables from your dataset, a logic expression, an -In the following example, the [CreateRule](https://docs.aws.amazon.com/frauddetector/latest/api/API_CreateRule.html) API is used to create three different rules: `high_risk`, `medium_risk`, and `low_risk`. Create rule expressions to compare the model performance score `sample_fraud_detection_model_insightscore` value against various thresholds. This is to determine the level of risk for an event and assign outcome that was defined in the previous step. +In the following example, the [CreateRule](https://docs.aws.amazon.com//frauddetector/latest/api/API_CreateRule.html) API is used to create three different rules: `high_risk`, `medium_risk`, and `low_risk`. Create rule expressions to compare the model performance score `sample_fraud_detection_model_insightscore` value against various thresholds. This is to determine the level of risk for an event and assign outcome that was defined in the previous step. @@ -292 +292 @@ A detector version defines model and rules that are used to get fraud prediction -In the following example, the [CreateDetectorVersion](https://docs.aws.amazon.com/frauddetector/latest/api/API_CreateDetectorVersion.html) API is used to create a detector version. It does this by providing model version details, rules, and a rule execution mode FIRST_MATCHED. A rule execution mode specifies the sequence for evaluating rules. The rule execution mode FIRST_MATCHED specifies that the rules are evaluated sequentially, first to last, stopping at first matched rule. +In the following example, the [CreateDetectorVersion](https://docs.aws.amazon.com//frauddetector/latest/api/API_CreateDetectorVersion.html) API is used to create a detector version. It does this by providing model version details, rules, and a rule execution mode FIRST_MATCHED. A rule execution mode specifies the sequence for evaluating rules. The rule execution mode FIRST_MATCHED specifies that the rules are evaluated sequentially, first to last, stopping at first matched rule. @@ -328 +328 @@ The last step of this tutorial uses the detector `sample_detector` created in th -In the following example, the [GetEventPrediction](https://docs.aws.amazon.com/frauddetector/latest/api/API_GetEventPrediction.html) API is used to provide data from a single account registration with each request. For this tutorial, take data (email_address and ip_address) from the account registration example data file. Each line (row) after the top header line represents data from a single account registration event. +In the following example, the [GetEventPrediction](https://docs.aws.amazon.com//frauddetector/latest/api/API_GetEventPrediction.html) API is used to provide data from a single account registration with each request. For this tutorial, take data (email_address and ip_address) from the account registration example data file. Each line (row) after the top header line represents data from a single account registration event.