Module Import alias identifier Import alias ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam NameParam defaults NameLoad NameLoad NameLoad Num body If CompareIs NameLoad NameLoad body Assign NameStore BinOpAdd BinOpAdd Call AttributeLoad AttributeLoad NameLoad attr attr SubscriptLoad AttributeLoad NameLoad attr Index Num Call AttributeLoad AttributeLoad NameLoad attr attr SubscriptLoad AttributeLoad NameLoad attr Index Num Call AttributeLoad AttributeLoad NameLoad attr attr SubscriptLoad AttributeLoad NameLoad attr Index Num Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr Assert CompareEq SubscriptLoad AttributeLoad NameLoad attr Index Num Num Str Assign NameStore Call AttributeLoad NameLoad attr Call AttributeLoad NameLoad attr Assign AttributeStore NameLoad attr Dict For NameStore NameLoad body Print BinOpMod Str NameLoad Assign NameStore Call AttributeLoad NameLoad attr Assign SubscriptStore NameLoad Index CompareNotEq Call AttributeLoad NameLoad attr NameLoad Num Assign SubscriptStore NameLoad Index CompareEq Call AttributeLoad NameLoad attr NameLoad Num Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad NameLoad keyword Call AttributeLoad NameLoad attr keyword NameLoad keyword NameLoad Expr Call AttributeLoad NameLoad attr keyword NameLoad Assign SubscriptStore AttributeLoad NameLoad attr Index NameLoad SubscriptLoad Call AttributeLoad NameLoad attr NameLoad Index Num Delete NameDel Delete NameDel decorator_list decorator_list
N/A N/A numpy np N/A GPy OneVsAllSparseClassification N/A object N/A N/A 
    Gaussian Process classification: One vs all

    This is a thin wrapper around the models.GPClassification class, with a set of sensible defaults

    :param X: input observations
    :param Y: observed values, can be None if likelihood is not None
    :param kernel: a GPy kernel, defaults to rbf

    .. Note:: Multiple independent outputs are not allowed

     __init__ N/A N/A self X Y kernel Y_metadata messages num_inducing N/A None None True 10 N/A N/A N/A kernel None N/A N/A kernel N/A N/A N/A N/A N/A GPy kern RBF N/A N/A X shape N/A 1 N/A N/A N/A GPy kern White N/A N/A X shape N/A 1 N/A N/A N/A GPy kern Bias N/A N/A X shape N/A 1 N/A likelihood N/A N/A N/A GPy likelihoods Bernoulli N/A N/A N/A N/A Y shape N/A 1 1 Y should be 1 column vector N/A labels N/A N/A np unique N/A N/A Y flatten N/A N/A self results N/A N/A yj labels N/A N/A N/A Class %s vs all yj N/A Ynew N/A N/A Y copy N/A N/A Ynew N/A N/A N/A N/A Y flatten yj 0 N/A N/A Ynew N/A N/A N/A N/A Y flatten yj 1 N/A m N/A N/A N/A GPy models SparseGPClassification X Ynew kernel N/A N/A kernel copy Y_metadata Y_metadata num_inducing num_inducing N/A N/A N/A m optimize messages messages N/A N/A N/A self results N/A yj N/A N/A N/A m predict X N/A 0 N/A m N/A Ynew N/A N/A