@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class AnomalyDetector extends Object implements Serializable, Cloneable
An anomaly detection model associated with a particular CloudWatch metric and statistic. You can use the model to display a band of expected normal values when the metric is graphed.
Constructor and Description |
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AnomalyDetector() |
Modifier and Type | Method and Description |
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AnomalyDetector |
clone() |
boolean |
equals(Object obj) |
AnomalyDetectorConfiguration |
getConfiguration()
The configuration specifies details about how the anomaly detection model is to be trained, including time ranges
to exclude from use for training the model, and the time zone to use for the metric.
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List<Dimension> |
getDimensions()
The metric dimensions associated with the anomaly detection model.
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String |
getMetricName()
The name of the metric associated with the anomaly detection model.
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String |
getNamespace()
The namespace of the metric associated with the anomaly detection model.
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String |
getStat()
The statistic associated with the anomaly detection model.
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String |
getStateValue()
The current status of the anomaly detector's training.
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int |
hashCode() |
void |
setConfiguration(AnomalyDetectorConfiguration configuration)
The configuration specifies details about how the anomaly detection model is to be trained, including time ranges
to exclude from use for training the model, and the time zone to use for the metric.
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void |
setDimensions(Collection<Dimension> dimensions)
The metric dimensions associated with the anomaly detection model.
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void |
setMetricName(String metricName)
The name of the metric associated with the anomaly detection model.
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void |
setNamespace(String namespace)
The namespace of the metric associated with the anomaly detection model.
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void |
setStat(String stat)
The statistic associated with the anomaly detection model.
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void |
setStateValue(String stateValue)
The current status of the anomaly detector's training.
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String |
toString()
Returns a string representation of this object.
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AnomalyDetector |
withConfiguration(AnomalyDetectorConfiguration configuration)
The configuration specifies details about how the anomaly detection model is to be trained, including time ranges
to exclude from use for training the model, and the time zone to use for the metric.
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AnomalyDetector |
withDimensions(Collection<Dimension> dimensions)
The metric dimensions associated with the anomaly detection model.
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AnomalyDetector |
withDimensions(Dimension... dimensions)
The metric dimensions associated with the anomaly detection model.
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AnomalyDetector |
withMetricName(String metricName)
The name of the metric associated with the anomaly detection model.
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AnomalyDetector |
withNamespace(String namespace)
The namespace of the metric associated with the anomaly detection model.
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AnomalyDetector |
withStat(String stat)
The statistic associated with the anomaly detection model.
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AnomalyDetector |
withStateValue(AnomalyDetectorStateValue stateValue)
The current status of the anomaly detector's training.
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AnomalyDetector |
withStateValue(String stateValue)
The current status of the anomaly detector's training.
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public void setNamespace(String namespace)
The namespace of the metric associated with the anomaly detection model.
namespace
- The namespace of the metric associated with the anomaly detection model.public String getNamespace()
The namespace of the metric associated with the anomaly detection model.
public AnomalyDetector withNamespace(String namespace)
The namespace of the metric associated with the anomaly detection model.
namespace
- The namespace of the metric associated with the anomaly detection model.public void setMetricName(String metricName)
The name of the metric associated with the anomaly detection model.
metricName
- The name of the metric associated with the anomaly detection model.public String getMetricName()
The name of the metric associated with the anomaly detection model.
public AnomalyDetector withMetricName(String metricName)
The name of the metric associated with the anomaly detection model.
metricName
- The name of the metric associated with the anomaly detection model.public List<Dimension> getDimensions()
The metric dimensions associated with the anomaly detection model.
public void setDimensions(Collection<Dimension> dimensions)
The metric dimensions associated with the anomaly detection model.
dimensions
- The metric dimensions associated with the anomaly detection model.public AnomalyDetector withDimensions(Dimension... dimensions)
The metric dimensions associated with the anomaly detection model.
NOTE: This method appends the values to the existing list (if any). Use
setDimensions(java.util.Collection)
or withDimensions(java.util.Collection)
if you want to
override the existing values.
dimensions
- The metric dimensions associated with the anomaly detection model.public AnomalyDetector withDimensions(Collection<Dimension> dimensions)
The metric dimensions associated with the anomaly detection model.
dimensions
- The metric dimensions associated with the anomaly detection model.public void setStat(String stat)
The statistic associated with the anomaly detection model.
stat
- The statistic associated with the anomaly detection model.public String getStat()
The statistic associated with the anomaly detection model.
public AnomalyDetector withStat(String stat)
The statistic associated with the anomaly detection model.
stat
- The statistic associated with the anomaly detection model.public void setConfiguration(AnomalyDetectorConfiguration configuration)
The configuration specifies details about how the anomaly detection model is to be trained, including time ranges to exclude from use for training the model, and the time zone to use for the metric.
configuration
- The configuration specifies details about how the anomaly detection model is to be trained, including time
ranges to exclude from use for training the model, and the time zone to use for the metric.public AnomalyDetectorConfiguration getConfiguration()
The configuration specifies details about how the anomaly detection model is to be trained, including time ranges to exclude from use for training the model, and the time zone to use for the metric.
public AnomalyDetector withConfiguration(AnomalyDetectorConfiguration configuration)
The configuration specifies details about how the anomaly detection model is to be trained, including time ranges to exclude from use for training the model, and the time zone to use for the metric.
configuration
- The configuration specifies details about how the anomaly detection model is to be trained, including time
ranges to exclude from use for training the model, and the time zone to use for the metric.public void setStateValue(String stateValue)
The current status of the anomaly detector's training. The possible values are
TRAINED | PENDING_TRAINING | TRAINED_INSUFFICIENT_DATA
stateValue
- The current status of the anomaly detector's training. The possible values are
TRAINED | PENDING_TRAINING | TRAINED_INSUFFICIENT_DATA
AnomalyDetectorStateValue
public String getStateValue()
The current status of the anomaly detector's training. The possible values are
TRAINED | PENDING_TRAINING | TRAINED_INSUFFICIENT_DATA
TRAINED | PENDING_TRAINING | TRAINED_INSUFFICIENT_DATA
AnomalyDetectorStateValue
public AnomalyDetector withStateValue(String stateValue)
The current status of the anomaly detector's training. The possible values are
TRAINED | PENDING_TRAINING | TRAINED_INSUFFICIENT_DATA
stateValue
- The current status of the anomaly detector's training. The possible values are
TRAINED | PENDING_TRAINING | TRAINED_INSUFFICIENT_DATA
AnomalyDetectorStateValue
public AnomalyDetector withStateValue(AnomalyDetectorStateValue stateValue)
The current status of the anomaly detector's training. The possible values are
TRAINED | PENDING_TRAINING | TRAINED_INSUFFICIENT_DATA
stateValue
- The current status of the anomaly detector's training. The possible values are
TRAINED | PENDING_TRAINING | TRAINED_INSUFFICIENT_DATA
AnomalyDetectorStateValue
public String toString()
toString
in class Object
Object.toString()
public AnomalyDetector clone()
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