Modifier and Type | Method and Description |
---|---|
org.wso2.carbon.ml.commons.domain.Workflow |
MLModelHandler.buildModel(int tenantId,
String userName,
long modelId)
Build a ML model asynchronously and persist the built model in a given storage.
|
Modifier and Type | Method and Description |
---|---|
abstract org.wso2.carbon.ml.commons.domain.MLModel |
MLModelBuilder.build()
Build a model using the context.
|
Modifier and Type | Method and Description |
---|---|
org.wso2.carbon.ml.commons.domain.MLModel |
SupervisedSparkModelBuilder.build()
Build a supervised model.
|
org.wso2.carbon.ml.commons.domain.MLModel |
DeeplearningModelBuilder.build() |
org.wso2.carbon.ml.commons.domain.MLModel |
AnomalyDetectionModelBuilder.build()
Build an KMeans Anomaly Detection model.
|
org.wso2.carbon.ml.commons.domain.MLModel |
UnsupervisedSparkModelBuilder.build()
Build an unsupervised model.
|
org.apache.spark.api.java.JavaRDD<org.apache.spark.mllib.regression.LabeledPoint> |
SupervisedSparkModelBuilder.preProcess() |
org.apache.spark.api.java.JavaPairRDD<Double,Double> |
StackedAutoencodersClassifier.test(org.apache.spark.api.java.JavaSparkContext ctxt,
hex.deeplearning.DeepLearningModel deeplearningModel,
org.apache.spark.api.java.JavaRDD<org.apache.spark.mllib.regression.LabeledPoint> test,
org.wso2.carbon.ml.commons.domain.MLModel mlModel)
This method applies a stacked autoencoders model to a given dataset and make predictions
|
Modifier and Type | Method and Description |
---|---|
org.wso2.carbon.ml.commons.domain.MLModel |
RecommendationModelBuilder.build()
Build a model using the context.
|
Modifier and Type | Method and Description |
---|---|
double[] |
Normalization.call(double[] values) |
String[] |
MeanImputation.call(String[] tokens) |
org.apache.spark.mllib.linalg.Vector |
TokensToVectors.call(String[] tokens) |
org.apache.spark.mllib.recommendation.Rating |
StringArrayToRating.call(String[] tokens) |
double[] |
StringArrayToDoubleArray.call(String[] tokens) |
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