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See:
Description
Class Summary |
Class | Description |
---|---|
ClassificationTestTask | An instance of ClassificationTestTask is used for
testing a model on test data. |
CrossValidateTask | An instance of CrossValidateTask provides an additional
technique for measuring the accuracy of a predictive model. |
MiningApplyTask | An instance of MiningApplyTask is used for
applying a model to a data set to make predictions, classifications, and
to provide associated probabilities. |
MiningBuildTask | An instance of MiningBuildTask is used for
building all mining models supported by ODM. |
MiningDataTask | The abstract class MiningDataTask is the common superclass
for all mining tasks that involve data mining
operations e.g, (building models, scoring(apply),
testing, cross-validate, lift computation). |
MiningLiftTask | An instance of MiningLiftTask is used to
compute the lift based on the specified positive target value and the
number of quantiles. |
MiningTask | The abstract class MiningTask is the common superclass for
all data mining task classes. |
MiningTaskStatus | An instance of MiningTaskStatus provides the following
details on the state of a tasks execution:
MiningTaskState enumeration
State entry timestamp
State description
A given task may have multiple MiningTaskStatus instances that provide
a status history for the task . |
ModelExportTask | An instance of ModelExportTask is used to export ODM mining models to standard format mining model
representations. |
ModelImportTask | An instance of ModelImportTask is used to import standard format mining models to the DMS. |
ModelSeekerTask | An instance of ModelSeekerTask
is a task used to invoke the Model Seeker functionality. |
Exception Summary |
Exception | Description |
---|---|
MiningTaskException | The exception MiningTaskException is thrown when there is
a failure during the execution of a mining task. |
This package contains Java classes representing mining tasks. Mining tasks are named objects that perform a designated mining operation asynchronously. A task object serves as a container within which to specify arguments to data mining operations to be performed by Oracle9i Data Mining. By providing an object to specify tasks, deferred (batch) processing of tasks is feasible. The task execution handle can be used to interrupt or terminate executing invocations. For deferred or batch processing, one or more task objects can be saved and scheduled for execution at a later time.
Note that each type of mining model also provides synchronous methods
for appropriate mining operations.
For example, ClusteringModel
provides static methods for build and apply.
Mining model classes also provides other static methods such as apply, test,
and compute lift (for supervised and clustering models), and for association
rules model, various rule retrieval methods.
ODM supports the following mining operations. Refer to the Concepts manual for more details.
MiningModel
is built in the data mining server (DMS).
After the model is built, it is persisted in the DMS and can be accessed by its
user specified unique name. Costs and priors may be provided when building a
classification model.
(Refer to MiningBuildTask
.)
ClusteringModel
to data results in, for each record,
a predicted cluster ID and the probability that the record is in that cluster.
The data to be scored must have attributes compatible with those of the training
data; it must have the same attributes with the same names and respective data
types or a suitable mapping.
The output of apply operation is placed in the schema specified by the user.
(Refer to MiningApplyOutput
and MiningApplyTask
.)
ODM supports the following types of mining task:
MiningBuiltTask
: performs model build operation with parameters
including an input data, a MiningFunctionSettings
,
and the name of the model
MiningApplyTask
: performs apply operation with parameters
including an input data, a model name to be applied, an apply
output specification and its location, and the name of the
apply result metadata.
ClassificationTestTask
: performs test mining operation
with parameters including an input data, a model name to be tested,
and the name of the test result metadata.
MiningLiftTask
: performs lift mining operation with parameters
including an input data, the number of quantiles, the positive
target values, a model name to be applied, and the name of the
lift result metadata.
CrossValidateTask
: performs cross validation mining operation
with parameters including an input data, a function settings name,
and the name of the result metadata.
This task effectively builds a NaiveBayesModel
and
runs cross validation against the model to measure the accuracy
of the model (using the same input data).
ModelSeekerTask
: used to build a set of models and performs
test and/or lift mining operations on them to find a better model.
ModelExportTask
: used to export a model as a PMML v2.0 string
and persist the string in a specified location.
Oracle9i Data Mining supports exporting association rules
models and naive bayes models into PMML v2.0.
ModelImportTask
: used to import a model of a specified type
and persist in the DMS with a designated name.
Oracle9i Data Mining supports importing association rules
models and naive bayes models in PMML v2.0.
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