support xgboost regression model#797
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Yancey0623 merged 1 commit intosql-machine-learning:developfrom Sep 10, 2019
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weiguoz
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Sep 9, 2019
| WITH | ||
| objective="reg:squarederror", | ||
| train.num_boost_round = 30 | ||
| COLUMN f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f11,f12,f13 |
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Thanks, will fix it in the next PR.
tonyyang-svail
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Sep 9, 2019
| # TODO(typhoonzero): regression models may have different behavior | ||
| pred_classes = np.argmax(np.array(preds), axis=1) | ||
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| # TODO(Yancey1989): using the train parameters to decide regressoin model or classifier model |
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how to get the train parameters? Should we add TrainIR to PredictIR?
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Maybe we can save the TrainClause in the model struct:
Lines 27 to 30 in 5ae82c0
And the prediction job can resolve the TrainClause to the parameters. And I think PredictIR is a good idea, do you want to resolve the Predict SQL and saved model into PredictIR?
typhoonzero
reviewed
Sep 10, 2019
| pred_classes = np.argmax(np.array(preds), axis=1) | ||
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| # TODO(Yancey1989): using the train parameters to decide regressoin model or classifier model | ||
| if len(preds.shape) == 2: |
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Should find a more accurate way to determine whether the model is a regression model.
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fixed #795