类 OnlineStandardScaler
- java.lang.Object
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- org.apache.flink.ml.feature.standardscaler.OnlineStandardScaler
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- 所有已实现的接口:
Serializable,org.apache.flink.ml.api.Estimator<OnlineStandardScaler,OnlineStandardScalerModel>,org.apache.flink.ml.api.Stage<OnlineStandardScaler>,org.apache.flink.ml.common.param.HasInputCol<OnlineStandardScaler>,org.apache.flink.ml.common.param.HasMaxAllowedModelDelayMs<OnlineStandardScaler>,org.apache.flink.ml.common.param.HasModelVersionCol<OnlineStandardScaler>,org.apache.flink.ml.common.param.HasOutputCol<OnlineStandardScaler>,HasWindows<OnlineStandardScaler>,OnlineStandardScalerModelParams<OnlineStandardScaler>,OnlineStandardScalerParams<OnlineStandardScaler>,StandardScalerParams<OnlineStandardScaler>,org.apache.flink.ml.param.WithParams<OnlineStandardScaler>
public class OnlineStandardScaler extends Object implements org.apache.flink.ml.api.Estimator<OnlineStandardScaler,OnlineStandardScalerModel>, OnlineStandardScalerParams<OnlineStandardScaler>
An Estimator which implements the online standard scaling algorithm, which is the online version ofStandardScaler.OnlineStandardScaler splits the input data by the user-specified window strategy (i.e.,
HasWindows). For each window, it computes the mean and standard deviation using the data seen so far (i.e., not only the data in the current window, but also the history data). The model data generated by OnlineStandardScaler is a model stream. There is one model data for each window.During the inference phase (i.e., using
OnlineStandardScalerModelfor prediction), users could output the model version that is used for predicting each data point. Moreover,- When the train data and test data both contain event time, users could specify the maximum
difference between the timestamps of the input and model data (
HasMaxAllowedModelDelayMs), which enforces to use a relatively fresh model for prediction. - Otherwise, the prediction process always uses the current model data for prediction.
- 另请参阅:
- 序列化表格
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字段概要
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从接口继承的字段 org.apache.flink.ml.common.param.HasWindows
WINDOWS
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从接口继承的字段 org.apache.flink.ml.feature.standardscaler.StandardScalerParams
WITH_MEAN, WITH_STD
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构造器概要
构造器 构造器 说明 OnlineStandardScaler()
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方法概要
所有方法 静态方法 实例方法 具体方法 修饰符和类型 方法 说明 OnlineStandardScalerModelfit(org.apache.flink.table.api.Table... inputs)Map<org.apache.flink.ml.param.Param<?>,Object>getParamMap()static OnlineStandardScalerload(org.apache.flink.table.api.bridge.java.StreamTableEnvironment tEnv, String path)voidsave(String path)-
从类继承的方法 java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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从接口继承的方法 org.apache.flink.ml.common.param.HasMaxAllowedModelDelayMs
getMaxAllowedModelDelayMs, setMaxAllowedModelDelayMs
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从接口继承的方法 org.apache.flink.ml.common.param.HasWindows
getWindows, setWindows
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从接口继承的方法 org.apache.flink.ml.feature.standardscaler.StandardScalerParams
getWithMean, getWithStd, setWithMean, setWithStd
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方法详细资料
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fit
public OnlineStandardScalerModel fit(org.apache.flink.table.api.Table... inputs)
- 指定者:
fit在接口中org.apache.flink.ml.api.Estimator<OnlineStandardScaler,OnlineStandardScalerModel>
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save
public void save(String path) throws IOException
- 指定者:
save在接口中org.apache.flink.ml.api.Stage<OnlineStandardScaler>- 抛出:
IOException
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getParamMap
public Map<org.apache.flink.ml.param.Param<?>,Object> getParamMap()
- 指定者:
getParamMap在接口中org.apache.flink.ml.param.WithParams<OnlineStandardScaler>
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load
public static OnlineStandardScaler load(org.apache.flink.table.api.bridge.java.StreamTableEnvironment tEnv, String path) throws IOException
- 抛出:
IOException
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