Usage

Here we provide tutorials on running FATE jobs:

Submitting jobs with Pipeline is recommended, here are some Jupyter Notebook with guided instructions:

• Upload Data with FATE-Pipeline
• Train & Predict Hetero SecureBoost with FATE-Pipeline
• Build NN models with FATE-Pipeline
• Upload & Train Hetero SecureBoost on Data with Match ID
• Upload & Train Hetero SecureBoost on Data with Meta
• Upload & Run An Intersection Task on Data with Multiple Match IDs

Submitting jobs without Pipeline is supported as well, which one should provide job configuration(s) in json format:

• Tutorial
• Upload data
• DSL conf setting

Models can be published with FATE Serving to Serving without FATE:

• publish model

And for those who want to run jobs in batches, ie. run algorithm tests, try using fate_test:

• FATE-Test Tutorial

To merge models from different roles and export as sklearn/LightGBM or PMML format, please refer to the tutorial below:

• Guide to Merging FATE Model

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Last update: 2023-01-03