84bc8d341e5a0a0d0b20b8acda58a33d72a2c23a,sklearn/svm/_base.py,BaseLibSVM,fit,#BaseLibSVM#Any#Any#Any#,107

Before Change

                             " Input is a {}x{} matrix."
                             .format(X.shape[0], X.shape[1]))

        if sample_weight.shape[0] > 0 and sample_weight.shape[0] != X.shape[0]:
            raise ValueError("sample_weight and X have incompatible shapes: "
                             "%r vs %r\n"
                             "Note: Sparse matrices cannot be indexed w/"

After Change

                             "boolean masks (use `indices=True` in CV)."
                             % (sample_weight.shape, X.shape))

        kernel = "precomputed" if callable(self.kernel) else self.kernel

        if kernel == "precomputed":
            // unused but needs to be a float for cython code that ignores
            // it anyway
            self._gamma = 0.
        elif isinstance(self.gamma, str):
            if self.gamma == "scale":
                // var = E[X^2] - E[X]^2 if sparse
                X_var = ((X.multiply(X)).mean() - (X.mean()) ** 2

Instances