microsoft / microsoft/qlib

IC issue: not consistent

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bug
Dominant language
Python
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Description

🐛 Bug Description

In detailed_workflow.ipynb, when compute scoreIC:

  1. pred_df = recorder.load_object("pred.pkl"), so the result is after learn_prossecer;
  2. label_df = dataset.prepare("test", col_set="label"), so the result is before learn_prossecer;
    they are not consistent to compute IC or any related.

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with detailed_workflow.ipynb and trace the two shown paths: recorder.load_object("pred.pkl") and dataset.prepare("test", col_set="label"), including where learn_prossecer is applied. Compare the data states used for IC calculation and define completion as making those states consistent, then verify the affected workflow.

Written by the indexing model from the issue text.

Assessment

Tech stack
jupyter-notebook, python
Domain
data, machine-learning
Issue type
Bug
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
32/100

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