Importance of decision tree hyperparameters on generalization

I encounter this error asking me to reshape the series. How could I resolve this?



I think that it is caused by X being a 1D dimensional array. Indeed, this is a bit ambuigous because 1D vector could mean a single sample and many features or many samples and a single feature. That’s why scikit-learn requests to provide a 2-D array of shape (n_samples, n_features) to remove the ambiguity.

The message tell you that:

  • use X.reshape(-1, 1) to have a shape of (n_samples, 1)
  • or X.reshape(1, -1) to have a shape of (1, n_features).
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