what is the failing test? please provide the full traceback.
On 24 Jul 2017 10:58 pm, "Sam Barnett" <sambarnet...@gmail.com> wrote:
> Dear scikit-learn developers,
>
> I am developing a transformer, named Sqizer, that has the ultimate goal
> of modifying a kernel for use with the sklearn.svm package. When given an
> input data array X, Sqizer.transform(X) should have as its output the
> Gram matrix for X using the modified version of the kernel. Here is the
> code for the class so far:
>
> class Sqizer(BaseEstimator, TransformerMixin):
>
> def __init__(self, C=1.0, kernel='rbf', degree=3, gamma=1,
> coef0=0.0, cut_ord_pair=(2,1)):
> self.C = C
> self.kernel = kernel
> self.degree = degree
> self.gamma = gamma
> self.coef0 = coef0
> self.cut_ord_pair = cut_ord_pair
>
> def fit(self, X, y=None):
> # Check that X and y have correct shape
> X, y = check_X_y(X, y)
> # Store the classes seen during fit
> self.classes_ = unique_labels(y)
>
> self.X_ = X
> self.y_ = y
> return self
>
> def transform(self, X):
>
> X = check_array(X, warn_on_dtype=True)
>
> """Returns Gram matrix corresponding to X, once sqized."""
> def kPolynom(x,y):
> return (self.coef0+self.gamma*np.inner(x,y))**self.degree
> def kGauss(x,y):
> return np.exp(-self.gamma*np.sum(np.square(x-y)))
> def kLinear(x,y):
> return np.inner(x,y)
> def kSigmoid(x,y):
> return np.tanh(self.gamma*np.inner(x,y) +self.coef0)
>
> def kernselect(kername):
> switcher = {
> 'linear': kPolynom,
> 'rbf': kGauss,
> 'sigmoid': kLinear,
> 'poly': kSigmoid,
> }
> return switcher.get(kername, "nothing")
>
> cut_off = self.cut_ord_pair[0]
> order = self.cut_ord_pair[1]
>
> from SeqKernel import hiSeqKernEval
>
> def getGram(Y):
> gram_matrix = np.zeros((Y.shape[0], Y.shape[0]))
> for row1ind in range(Y.shape[0]):
> for row2ind in range
>
>
> _______________________________________________
> scikit-learn mailing list
> scikit-learn@python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
> ...
_______________________________________________
scikit-learn mailing list
scikit-learn@python.org
https://mail.python.org/mailman/listinfo/scikit-learn
