<p>Creates the configuration for training a model. A trained model is known as a solution. After the configuration is created, you train the model (create a solution) by calling the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_CreateSolutionVersion.html">CreateSolutionVersion</a> operation. Every time you call <code>CreateSolutionVersion</code>, a new version of the solution is created.</p> <p>After creating a solution version, you check its accuracy by calling <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_GetSolutionMetrics.html">GetSolutionMetrics</a>. When you are satisfied with the version, you deploy it using <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_CreateCampaign.html">CreateCampaign</a>. The campaign provides recommendations to a client through the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html">GetRecommendations</a> API.</p> <p>To train a model, Amazon Personalize requires training data and a recipe. The training data comes from the dataset group that you provide in the request. A recipe specifies the training algorithm and a feature transformation. You can specify one of the predefined recipes provided by Amazon Personalize. Alternatively, you can specify <code>performAutoML</code> and Amazon Personalize will analyze your data and select the optimum USER_PERSONALIZATION recipe for you.</p> <note> <p>Amazon Personalize doesn't support configuring the <code>hpoObjective</code> for solution hyperparameter optimization at this time.</p> </note> <p> <b>Status</b> </p> <p>A solution can be in one of the following states:</p> <ul> <li> <p>CREATE PENDING &gt; CREATE IN_PROGRESS &gt; ACTIVE -or- CREATE FAILED</p> </li> <li> <p>DELETE PENDING &gt; DELETE IN_PROGRESS</p> </li> </ul> <p>To get the status of the solution, call <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolution.html">DescribeSolution</a>. Wait until the status shows as ACTIVE before calling <code>CreateSolutionVersion</code>.</p> <p class="title"> <b>Related APIs</b> </p> <ul> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutions.html">ListSolutions</a> </p> </li> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_CreateSolutionVersion.html">CreateSolutionVersion</a> </p> </li> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolution.html">DescribeSolution</a> </p> </li> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DeleteSolution.html">DeleteSolution</a> </p> </li> </ul> <ul> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutionVersions.html">ListSolutionVersions</a> </p> </li> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html">DescribeSolutionVersion</a> </p> </li> </ul>

{
  "success": true,
  "data": {
    "id": "abc123",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

{
  "success": false,
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid request parameters"
  }
}

<p>Creates the configuration for training a model. A trained model is known as a solution. After the configuration is created, you train the model (create a solution) by calling the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_CreateSolutionVersion.html">CreateSolutionVersion</a> operation. Every time you call <code>CreateSolutionVersion</code>, a new version of the solution is created.</p> <p>After creating a solution version, you check its accuracy by calling <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_GetSolutionMetrics.html">GetSolutionMetrics</a>. When you are satisfied with the version, you deploy it using <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_CreateCampaign.html">CreateCampaign</a>. The campaign provides recommendations to a client through the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_RS_GetRecommendations.html">GetRecommendations</a> API.</p> <p>To train a model, Amazon Personalize requires training data and a recipe. The training data comes from the dataset group that you provide in the request. A recipe specifies the training algorithm and a feature transformation. You can specify one of the predefined recipes provided by Amazon Personalize. Alternatively, you can specify <code>performAutoML</code> and Amazon Personalize will analyze your data and select the optimum USER_PERSONALIZATION recipe for you.</p> <note> <p>Amazon Personalize doesn't support configuring the <code>hpoObjective</code> for solution hyperparameter optimization at this time.</p> </note> <p> <b>Status</b> </p> <p>A solution can be in one of the following states:</p> <ul> <li> <p>CREATE PENDING &gt; CREATE IN_PROGRESS &gt; ACTIVE -or- CREATE FAILED</p> </li> <li> <p>DELETE PENDING &gt; DELETE IN_PROGRESS</p> </li> </ul> <p>To get the status of the solution, call <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolution.html">DescribeSolution</a>. Wait until the status shows as ACTIVE before calling <code>CreateSolutionVersion</code>.</p> <p class="title"> <b>Related APIs</b> </p> <ul> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutions.html">ListSolutions</a> </p> </li> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_CreateSolutionVersion.html">CreateSolutionVersion</a> </p> </li> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolution.html">DescribeSolution</a> </p> </li> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DeleteSolution.html">DeleteSolution</a> </p> </li> </ul> <ul> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutionVersions.html">ListSolutionVersions</a> </p> </li> <li> <p> <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html">DescribeSolutionVersion</a> </p> </li> </ul>

{
  "success": true,
  "data": {
    "id": "abc123",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

{
  "success": false,
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid request parameters"
  }
}