130cbadff294b686e466d430f26b2d069f6bbf59,metric_learn/mlkr.py,MLKR,fit,#MLKR#Any#Any#,85

Before Change

      if A is None:
          // initialize to PCA transformation matrix
          // note: not the same as n_components=m !
          A = PCA().fit(X).components_.T[:m]
      elif A.shape != (m, d):
          raise ValueError("A0 needs shape (%d,%d) but got %s" % (
              m, d, A.shape))

After Change

      if m is None:
          m = d
      // if the init is the default (identity), we raise a warning just in case
      if self.init is None:
        // TODO:
        //  replace init=None by init="auto" in v0.6.0 and remove the warning
        msg = ("Warning, no init was set (`init=None`). As of version 0.5.0, "
               "the default init will now be set to "auto", instead of "pca". "
               "If you still want to use PCA as an init, set init="pca". "
               "This warning will disappear in v0.6.0, and `init` parameter"s"
               " default value will be set to "auto".")
        warnings.warn(msg, ChangedBehaviorWarning)
        init = "auto"
      else:
        init = self.init
      A = _initialize_transformer(m, X, y, init=init,
                                  random_state=self.random_state,
                                  // MLKR works on regression targets:
                                  has_classes=False)

Instances