public java.util.List<AutoMLAlgorithmConfig> getAlgorithmsConfig() {
        return algorithmsConfig;
    }
<p>
Your Autopilot job trains a default set of algorithms on your dataset. For tabular and time-series data, you can
customize the algorithm list by selecting a subset of algorithms for your problem type.
</p>
<p>
<code>AlgorithmsConfig</code> stores the customized selection of algorithms to train on your data.
</p>
<ul>
<li>
<p>
<b>For the tabular problem type <code>TabularJobConfig</code>,</b> the list of available algorithms to choose
from depends on the training mode set in <a
href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLJobConfig.html">
<code>AutoMLJobConfig.Mode</code> </a>.
</p>
<ul>
<li>
<p>
<code>AlgorithmsConfig</code> should not be set when the training mode <code>AutoMLJobConfig.Mode</code> is set
to <code>AUTO</code>.
</p>
</li>
<li>
<p>
When <code>AlgorithmsConfig</code> is provided, one <code>AutoMLAlgorithms</code> attribute must be set and one
only.
</p>
<p>
If the list of algorithms provided as values for <code>AutoMLAlgorithms</code> is empty,
<code>CandidateGenerationConfig</code> uses the full set of algorithms for the given training mode.
</p>
</li>
<li>
<p>
When <code>AlgorithmsConfig</code> is not provided, <code>CandidateGenerationConfig</code> uses the full set of
algorithms for the given training mode.
</p>
</li>
</ul>
<p>
For the list of all algorithms per training mode, see <a
href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLAlgorithmConfig.html">
AlgorithmConfig</a>.
</p>
<p>
For more information on each algorithm, see the <a href=
"https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-support"
>Algorithm support</a> section in the Autopilot developer guide.
</p>
</li>
<li>
<p>
<b>For the time-series forecasting problem type <code>TimeSeriesForecastingJobConfig</code>,</b> choose your
algorithms from the list provided in <a
href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLAlgorithmConfig.html">
AlgorithmConfig</a>.
</p>
<p>
For more information on each algorithm, see the <a
href="https://docs.aws.amazon.com/sagemaker/latest/dg/timeseries-forecasting-algorithms.html">Algorithms support
for time-series forecasting</a> section in the Autopilot developer guide.
</p>
<ul>
<li>
<p>
When <code>AlgorithmsConfig</code> is provided, one <code>AutoMLAlgorithms</code> attribute must be set and one
only.
</p>
<p>
If the list of algorithms provided as values for <code>AutoMLAlgorithms</code> is empty,
<code>CandidateGenerationConfig</code> uses the full set of algorithms for time-series forecasting.
</p>
</li>
<li>
<p>
When <code>AlgorithmsConfig</code> is not provided, <code>CandidateGenerationConfig</code> uses the full set of
algorithms for time-series forecasting.
</p>
</li>
</ul>
</li>
</ul>

@return Your Autopilot job trains a default set of algorithms on your dataset. For tabular and time-series data,
        you can customize the algorithm list by selecting a subset of algorithms for your problem type.</p>
        <p>
        <code>AlgorithmsConfig</code> stores the customized selection of algorithms to train on your data.
        </p>
        <ul>
        <li>
        <p>
        <b>For the tabular problem type <code>TabularJobConfig</code>,</b> the list of available algorithms to
        choose from depends on the training mode set in <a
        href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLJobConfig.html">
        <code>AutoMLJobConfig.Mode</code> </a>.
        </p>
        <ul>
        <li>
        <p>
        <code>AlgorithmsConfig</code> should not be set when the training mode <code>AutoMLJobConfig.Mode</code>
        is set to <code>AUTO</code>.
        </p>
        </li>
        <li>
        <p>
        When <code>AlgorithmsConfig</code> is provided, one <code>AutoMLAlgorithms</code> attribute must be set
        and one only.
        </p>
        <p>
        If the list of algorithms provided as values for <code>AutoMLAlgorithms</code> is empty,
        <code>CandidateGenerationConfig</code> uses the full set of algorithms for the given training mode.
        </p>
        </li>
        <li>
        <p>
        When <code>AlgorithmsConfig</code> is not provided, <code>CandidateGenerationConfig</code> uses the full
        set of algorithms for the given training mode.
        </p>
        </li>
        </ul>
        <p>
        For the list of all algorithms per training mode, see <a
        href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLAlgorithmConfig.html">
        AlgorithmConfig</a>.
        </p>
        <p>
        For more information on each algorithm, see the <a href=
        "https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-support"
        >Algorithm support</a> section in the Autopilot developer guide.
        </p>
        </li>
        <li>
        <p>
        <b>For the time-series forecasting problem type <code>TimeSeriesForecastingJobConfig</code>,</b> choose
        your algorithms from the list provided in <a
        href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLAlgorithmConfig.html">
        AlgorithmConfig</a>.
        </p>
        <p>
        For more information on each algorithm, see the <a
        href="https://docs.aws.amazon.com/sagemaker/latest/dg/timeseries-forecasting-algorithms.html">Algorithms
        support for time-series forecasting</a> section in the Autopilot developer guide.
        </p>
        <ul>
        <li>
        <p>
        When <code>AlgorithmsConfig</code> is provided, one <code>AutoMLAlgorithms</code> attribute must be set
        and one only.
        </p>
        <p>
        If the list of algorithms provided as values for <code>AutoMLAlgorithms</code> is empty,
        <code>CandidateGenerationConfig</code> uses the full set of algorithms for time-series forecasting.
        </p>
        </li>
        <li>
        <p>
        When <code>AlgorithmsConfig</code> is not provided, <code>CandidateGenerationConfig</code> uses the full
        set of algorithms for time-series forecasting.
        </p>
        </li>
        </ul>
        </li>
aws-java-sdk-sagemaker/src/main/java/com/amazonaws/services/sagemaker/model/CandidateGenerationConfig.java