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(len(x_train), ))) y_result = clf.predict(x.reshape(len(x), )) plt.plot(x, y, label='actual results') plt.plot(x, y_result, label='model predicts') plt.legend() plt.show() python scikit-learn decision-trees share | improve this question edited hours ago nathan asked hours ago nathan nathan bronze badges
are several packages in r for this: partyfit (and the older simpler party), mob, cubist; unfortunately, there don't seem to be any in python yet. here's a discussion on including it in sklearn, from mid- . share | improve this answer answered hours ago ben reiniger ben reiniger gold badge silver badges...
https://datascience.stackexchange.com/questions/65585/decision-tree-with-final-decision-being-a-linear-regression