This documentation is for Machine Learner 1.1.0. View documentation for the latest release.

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  1.   Log in to the WSO2 ML UI, if you are not already logged in. 
  2. Click PROJECTS in the top menu as shown below. 

  3. Click on the project in which you need to create the analysis.
  4. Enter a name for the analysis, and click CREATE ANALYSIS as shown below. 
  5. Enter details in the Step 1 - Preprocess as shown below. You can browse for a certain feature using the Search option provided.


    Specify the following details for each feature as preferred:

    • Include - If the feature should be included in the model or not.
    • Type - Whether the feature is of the type numerical or categorical.
    • Impute - Whether to impute missing values of a data row by discarding it or replacing it with the mean. In a dataset, an empty space, value NA or ? (question mark) are considered as missing values.

  6. Click Next.
  7. Enter details in the  Step 2 - Explore  as shown below. For more information on exploring data, see  Exploring Data.


    This step visualizes different aspects of the dataset using several chart types (i.e. scatter plot, parallel sets, trellis chart, and cluster diagram). All these chart types might not be available for all datasets due to feature types.

  8. Click Next.
  9. Enter details in the  Step 3 - Algorithms  as shown below.


    Select an algorithm to use for the model, and the response variable from the drop down list. Set the proportion of the dataset to be used for training for Train data fraction field.

  10. Click Next.
  11. Enter details in the  Step 4 - Parameters  as shown below.


    Set hyper-parameters of the selected algorithm. These hyper-parameters are already set with default values. Therefore, you can either opt to keep those values, or modify them as desired.

  12. Click Next.
  13. Enter details in the  Step 5 - Model  as shown below.


    Select the version of the dataset which to use to train the model.

  14. Clicking Runto build the model. As a result, the model training starts in the background and a list of all the models of the analysis is displayed as shown below.

    Once the model building completes, you can perform the below actions on that model. 

    • VIEW -  To view the summary of that model. You view relevant visualizations and tables according to the training algorithm as shown below. 
    • PREDICT - To make predictions on the model. 
    • DOWNLOAD - To prompt the download window, so that you can locally save the model in a preferred location. 
    • PUBLISH - To publish the model into WSO2 ML registry. A model can be published as a serialised model or in PMML format.
    • DELETE - To permanently delete the model.

Creating a new model within an analysis
New Model
New Model

Follow the steps below to create a new model for the same analysis using another version of the dataset, while all the other configurations remain the same.