Shellmiao 9279d1873b Add projects il y a 1 an
..
README.md 9279d1873b Add projects il y a 1 an
local_baseline_testsuite.json 9279d1873b Add projects il y a 1 an
test_local_baseline_homo_job_conf.json 9279d1873b Add projects il y a 1 an
test_local_baseline_homo_job_dsl.json 9279d1873b Add projects il y a 1 an
test_local_baseline_homo_predict_job_conf.json 9279d1873b Add projects il y a 1 an
test_local_baseline_homo_predict_job_dsl.json 9279d1873b Add projects il y a 1 an
test_local_baseline_job_conf.json 9279d1873b Add projects il y a 1 an
test_local_baseline_job_dsl.json 9279d1873b Add projects il y a 1 an
test_local_baseline_predict_job_conf.json 9279d1873b Add projects il y a 1 an
test_local_baseline_predict_job_dsl.json 9279d1873b Add projects il y a 1 an
test_local_baseline_sample_weight_job_conf.json 9279d1873b Add projects il y a 1 an
test_local_baseline_sample_weight_job_dsl.json 9279d1873b Add projects il y a 1 an

README.md

Local Baseline Configuration Usage Guide.

Example Tasks

This section introduces the dsl and conf for different types of tasks.

  1. Hetero Train Task:

    dsl: test_local_baseline_job_dsl.json

    runtime_config : test_local_baseline_job_conf.json

    data type: multi-class label

  2. Hetero Predict Task:

    dsl: test_local_baseline_predict_job_dsl.json

    runtime_config : test_local_baseline_predict_job_conf.json

    data type: multi-class label

  3. Homo Train Task:

    dsl: test_local_baseline_homo_job_dsl.json

    runtime_config : test_local_baseline_homo_job_conf.json

    data type: binary label

  4. Homo Predict Task:

    dsl: test_local_baseline_homo_predict_job_dsl.json

    runtime_config : test_local_baseline_homo_predict_job_conf.json

    data type: binary label

  5. Hetero Train Task with Sample Weight:

    dsl: test_local_baseline_job_dsl.json

    runtime_config : test_local_baseline_sample_weight_job_conf.json

    data type: multi-class label

Users can use following commands to run the task.

flow job submit -c ${runtime_config} -d ${dsl}

After having finished a successful training task, you can use FATE Board to check model output and evaluation results.