MEDomicsLab-docs
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  • 👋Welcome!
  • 👊Quick start
  • 👀Overview
  • 🧑‍🏫Tutorials
    • 🔵Design
      • Extraction Module
        • Image Extraction Page
        • Text Extraction Page
        • Time Series Extraction Page
        • MEDimage
      • Input Module
        • Feature Reduction Tool
        • MEDprofiles
          • MEDprofiles Viewer
      • Exploratory Module
    • 🟠Development
      • Learning Module
      • Evaluation Module
      • Federated Learning Module
        • Overview
        • Configure database
        • Create pipelines
        • Pipeline results
        • Hyperparameters optimization
        • Merge results
        • Crash tutorial
    • 🟢Deployment
      • Application Module
    • 🛠️Miscellaneous
  • 📄Testing Phase with MIMIC
    • MIMIC data access
    • Step 1: Install and Explore
    • Step 2: Extract Data
    • Step 3: Prepare ML tables
    • Step 4: Explore Data
    • Step 5: Vacations
    • Step 6: Create Model
    • Step 7: Evaluate & Apply Model
    • Step 8: Challenge
    • Wrap-Up
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On this page
  • Video tutorial
  • Steps
  • 1. Creating the workspace:
  • 2. Uploading Datasets:
  • 3. Configuring Database:
  • 4. Optimizing hyperparameters:
  • 5. Creating and running pipelines
  • 6. Pipeline results
  • 7. Merge results
  1. Tutorials
  2. Development
  3. Federated Learning Module

Crash tutorial

PreviousMerge resultsNextDeployment

On this page, we will apply everything we've covered in the previous tutorials. We will start from scratch and guide you through the final steps of viewing and saving the results.

Video tutorial

Steps

1. Creating the workspace:

When you first open the MedomicsLab application, you see this window where we can view our previously created workspaces. In my case, there is an old workspace, but if you are new to this application, you should click the 'Set workspace' button and choose a folder. It's preferable to choose an empty folder.

2. Uploading Datasets:

For this experience, we will need a dataset to run the pipelines, so we need to add the datasets to the workspace.

MEDfl supports numerical tabular datasets. If you want to test your dataset, ensure it is compatible and clean. It's always preferable to start the tutorial with our provided dataset for consistency.

3. Configuring Database:

When you first open MEDfl, you'll see a popup containing instructions on how to create a configuration file. This file will be used to connect to the MySQL database on your local machine.

To get started, create a file named config.ini in your workspace and add your connection information, including the username and password.

[mysql]
host = localhost
port = 3306
user = YOUR_SQL_USERNAME
password = YOUR_PASSWORD
database = MEDfl

4. Optimizing hyperparameters:

Before we create the pipeline, we can optimize the model hyperparameters to improve performance.

After the optimization, we can use the results to initialize the central model hyperparameters.

After Having the optimization results we will save them, so we can use them later

5. Creating and running pipelines

6. Pipeline results

You can switch between different configuration results and also between different types of results. There are mainly three types of results: Global results, results by node, and compare results.

7. Merge results

In this section, we will merge two different result files into one file containing both sets of results.

You have the option to add the "Merge Results" node separately from the pipeline, or you can link it to the pipeline so that the pipeline results will be automatically merged with the specified file.

For our example, we will use the . Make sure to download the files, and once you have them, add them to the DATA folder and refresh the workspace.

for more details about configuring the database feel free to check

For our example, we will use the Optuna central optimization to optimize the hyperparameters. MEDfl offers various options for optimization, so feel free to check the for more details.

for this experience, we will create two configurations and run them simultaneously, each configuration will have a different aggregation algorithm for more details on how to create the pipeline and add the different nodes please check

After the execution of the pipelines, you will have the option to see results by clicking on the "See results" button .

For more details about the results, refer to the .

To save the results, click on the "Save" button and an input field will appear where you can enter the file name . After confirming, two types of files will be created, and you can open them directly by clicking on them.

🧑‍🏫
🟠
Diabetes dataset
the configuration tutorial page
Optimization tutorial page
this tutorial page
Pipeline Results tutorial page