[MRG] Example for multioutput.RegressorChain #15215
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@adrinjalali open |
adrinjalali
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Mar 2, 2020
| >>> from sklearn.multioutput import RegressorChain | ||
| >>> from sklearn.linear_model import LogisticRegression | ||
| >>> logreg = LogisticRegression(solver='lbfgs',multi_class='multinomial') | ||
| >>> X, Y = [[1,0],[0,1],[1,1]], [[0,2],[1,1],[2,0]] |
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| >>> X, Y = [[1,0],[0,1],[1,1]], [[0,2],[1,1],[2,0]] | |
| >>> X, Y = [[1, 0], [0, 1], [1, 1]], [[0, 2], [1, 1], [2, 0]] |
| >>> from sklearn.linear_model import LogisticRegression | ||
| >>> logreg = LogisticRegression(solver='lbfgs',multi_class='multinomial') | ||
| >>> X, Y = [[1,0],[0,1],[1,1]], [[0,2],[1,1],[2,0]] | ||
| >>> chain = RegressorChain(base_estimator=logreg,order=[0,1]).fit(X,Y) |
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| >>> chain = RegressorChain(base_estimator=logreg,order=[0,1]).fit(X,Y) | |
| >>> chain = RegressorChain(base_estimator=logreg, order=[0, 1]).fit(X, Y) |
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@adrinjalali no, I don't think so
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@timnon do you plan to continue working on this PR? |
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take |
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take |
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Reference Issues/PRs
Issue #3846
What does this implement/fix? Explain your changes.
Example for
multioutput.RegressorChainAny other comments?
The naming of this class is wrong, it should be
MultiLabelClassifierChain, it is not a regression but a multi-label classification