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The <ML_HOME>/repository/conf/machine-learner.xml file includes all the ML-specific configurations.
How can I change the ML datasource name?
The default name is jdbc/WSO2ML_DB. You can change it by changing the value of the <DataSourceName> element in the <ML_HOME>/repository/conf/machine-learner.xml file. For more information, see ML-specific configurations.
How can I change the sample points size that ML use to generate summary statistics?
Default size is 10000. You can change it by changing the value of the <SampleSize> property within the <SummaryStatisticsSettings> element in the <ML_HOME>/repository/conf/machine-learner.xml file. For more information, see ML-specific configurations.
How can I change the directory which holds datasets?
By default, the <ML_HOME>/datasets/ directory holds datasets, and the default storage type is ‘file’. You can change it by changing the value of the <StorageDirectory> property within the <DatasetStorage> element in the <ML_HOME>/repository/conf/machine-learner.xml file. For more information, see ML-specific configurations.
How can I change the directory with models?
By default, the <ML_HOME>/models/ directory holds models, and default storage type is ‘file’. You can change it by changing the value of the <StorageDirectory> property within the <ModelStorage> element in the <ML_HOME>/repository/conf/machine-learner.xml file. For more information, see ML-specific configurations.
How can I increase ML thread pool size?
WSO2 ML uses threads in a thread pool to run different tasks such as dataset summary generation and model generation etc. You can control the size of this thread pool by changing the value of the following property in the <ML_HOME>/repository/conf/machine-learner.xml file: <Property name="ml.thread.pool.size" value="100"/> For more information, see ML-specific configurations.
Where should I configure the email addresses of recipients whom will be notified upon a model generation?
You can configure WSO2 ML to send emails on the completion of a model generation. You can have a comma-separated set of email addresses as the value of the <EmailNotificationEndpoint> property in the <ML_HOME>/repository/conf/machine-learner.xml file. For more information on configuring email support, see Enabling Email Notifications.
How can I change datasets storage to HDFS?
If you want to change the dataset storage type to HDFS, change the value of the <StorageType> property within the <DatasetStorage> element to ‘hdfs’. For more information, see ML-specific configurations.
How can I change model storage to HDFS?
If you want to change the model storage type to HDFS, change the value of the <StorageType> property within the <ModelStorage> element to ‘hdfs’. For more information, see ML-specific configurations.
How can I give a HDFS URL?
If you want to store your datasets and models in an HDFS, you need to enter HDFS URL as the value of the <HdfsURL> property in the <ML_HOME>/repository/conf/machine-learner.xml file. For more information, see ML-specific configurations.
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Data related questions
What should be the format of my dataset?
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It is not mandatory to have a header row. If the dataset does not have a header row, it will be indicated when you upload the dataset. Then WSO2 ML will generate a header similar to V1, V2 .. Vn. See Creating a Dataset for For more information see Exploring Data.
Is there a file size limit to my dataset?
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How can I find the details of a built model?
Once you built a model, you can view its model summary, in which you find a summary of the model evaluation. For more information, see Evaluating Models.
How can I calculate the accuracy for a given model?
For classification type algorithms, generate an accuracy measurement based on the predictions made by the model for the test dataset. Test dataset is extracted from the uploaded dataset and the proportion is configurable for each analyses.
Can I download a built model?
You can download a built model or publish it to WSO2 registry. For more information, see Generating Models.
Do you support exporting models in PMML format?
WSo2 ML 1.0.0 does not support PMML format. This is in the roadmap to be provided in future versions.
Can I use a built model in a Java program?
You can use a built model in a Java program. For a sample on how to use a built model in a Java program, see Using ML Models in a Java Client.
How can I make predictions for a test dataset using ML UI wizard?
Once you build a model, you can make predictions to a test dataset by uploading a csv/tsv file from the Predict page in the ML UI. For more information on making predictions, see Making Predictions Using the ML UI.
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WSO2 ML REST API root context is ‘/ml’. For more information, see REST API Guide.
What authentication mechanisms you support?
WSO2 ML supports basic authentication and cookie based authentication. For more information, see REST API Guide.
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