aima/learning.py
def setproblem(self, target, inputs=None, exclude=()):
        """Set (or change) the target and/or inputs.
        This way, one DataSet can be used multiple ways. inputs, if specified,
        is a list of attributes, or specify exclude as a list of attributes
        to not use in inputs. Attributes can be -n .. n, or an attrname.
        Also computes the list of possible values, if that wasn't done yet."""
        self.target = self.attrnum(target)
        exclude = map(self.attrnum, exclude)
        if inputs:
            self.inputs = removeall(self.target, inputs)
        else:
            self.inputs = [a for a in self.attrs
                           if a != self.target and a not in exclude]
        if not self.values:
            self.values = map(unique, zip(*self.examples))
        self.check_me()
def setproblem(self, target, inputs=None, exclude=()):
        """Set (or change) the target and/or inputs.
        This way, one DataSet can be used multiple ways. inputs, if specified,
        is a list of attributes, or specify exclude as a list of attributes
        to not use in inputs. Attributes can be -n .. n, or an attrname.
        Also computes the list of possible values, if that wasn't done yet."""
        self.target = self.attrnum(target)
        exclude = map(self.attrnum, exclude)
        if inputs:
            self.inputs = removeall(self.target, inputs)
        else:
            self.inputs = [a for a in self.attrs
                           if a != self.target and a not in exclude]
        if not self.values:
            self.values = map(unique, zip(*self.examples))
        self.check_me()
Set (or change) the target and/or inputs.
        This way, one DataSet can be used multiple ways. inputs, if specified,
        is a list of attributes, or specify exclude as a list of attributes
        to not use in inputs. Attributes can be -n .. n, or an attrname.
        Also computes the list of possible values, if that wasn't done yet.