Generates a classifier model that is used by tPredict to
classify given elements.
tNaiveBayesModel analyzes incoming datasets based on applying Bayes’ law
with the (naive) assumption that the analyzed features of an element are independent of each
It generates a classification model out of this analysis and writes
this model in a given file system in the PMML (Predictive Model Markup
In local mode, Apache Spark 1.3.0, 1.4.0, 1.5.0, 1.6.0, 2.0.0, 2.3.0 and 2.4.0 are
tNaiveBayesModel properties for Apache Spark Batch
These properties are used to configure tNaiveBayesModel running in the Spark Batch Job framework.
The Spark Batch
tNaiveBayesModel component belongs to the Machine Learning family.
Define a storage configuration
Select the configuration component to be used to provide the configuration
If you leave this check box clear, the target file system is the local
The configuration component to be used must be present in the same Job.
Select the Spark version you are using.
For Spark V1.4 onwards, the parameters to be set are:
For Spark 1.3, see the parameters explained in the following rows of
Complete this table to define the feature type of each input column in
order to compute the classifier model.
Enter the percentage (expressed in the decimal form) of the input data
PMML model path
Enter the directory in which you need to store the generated
The button for browsing does not work with the Spark
For further information about the PMML format used by Naive Bayes
Parquet model name
Enter the name you need to use for the classifier model.
This component is used as an end component and requires an input link.
The parameters you need to set are free parameters and so their values
Therefore, you need to train the classifier model you are generating
These scores can be output to the console of the Run view
when you execute the Job when you have added the following code to the Log4j view in the Project Settings dialog
These scores are output along with the other Log4j INFO-level information. If you want to
If you are using a subscription-based version of the Studio, the activity of this
For more information on the log4j logging levels, see the Apache documentation at http://logging.apache.org/log4j/1.2/apidocs/org/apache/log4j/Level.html.
No scenario is available for the Spark Batch version of this component