[ENH] OnlineBatchMixture online regression

[patelchaitany]

Reference Issues/PRs

Implemented OnlineBatchMixture from Issue #464

What does this implement/fix? Explain your changes.

Adds OnlineBatchMixture, an online regression strategy that fits a separate regressor clone on each incoming batch and returns a Mixture of predictions weighted by sample counts.

Supports a min_batch_size threshold with two modes: "accumulate" (buffer small batches) or "discard" (drop them).

Here is small example

  from skpro.regression.online import OnlineBatchMixture
  from skpro.regression.residual import ResidualDouble
  from sklearn.linear_model import LinearRegression
  from sklearn.datasets import load_diabetes
  from sklearn.model_selection import train_test_split
  
  X, y = load_diabetes(return_X_y=True, as_frame=True)
  X_train, X_test, y_train, y_test = train_test_split(X, y)
  
  reg_proba = ResidualDouble(LinearRegression())
  online = OnlineBatchMixture(reg_proba, min_batch_size=30)
  online.fit(X_train[:200], y_train[:200])
  online.update(X_train[200:], y_train[200:])
  y_pred = online.predict_proba(X_test)

Does your contribution introduce a new dependency? If yes, which one?

No

What should a reviewer concentrate their feedback on?

Did you add any tests for the change?

Any other comments?

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[patelchaitany]

@fkiraly, @felipeangelimvieira could you plz review it.

[fkiraly]

Very nice!

I left some small change requests.

[fkiraly]

You have not addressed my change requests.

Please ensure you also comment on change requests: either you carry them out and say so, or you ask for clarification, or you argue why you think it should not be made (e.g., out of scope).

[fkiraly]

Very nice!