def closest(i, arr):
"""
:param arr: np array (len=No. Indep var + No. Depen var)
:return: float
"""
return sorted(i.clstr,
key=lambda x: edist(arr.sample[:-1], x.sample[:-1]))
def envy(self, testCase, alpha=0.5):
me = self.closest(testCase)
others = [o for o in self.clusters if not me == o]
betters = [f for f in others if f.exemplar()[-1] < alpha*me.exemplar()[-1]]
try:
return sorted([f for f in betters],
key=lambda F: edist(F.exemplar()/self.norm, me.exemplar()/self.norm))[0]
except:
return me
def closest(i, arr): """ :param arr: np array (len=No. Indep var + No. Depen var) :return: float """ return sorted(i.clstr, key= lambda x: edist(arr[:-1], x.sample[:-1]))
def proj(one, two, test): a = edist(one, test) b = edist(two, test) c = edist(one, two) return (a**2-b**2+c**2)/(2*c)
def proj(one, two, test):
a = edist(one, test)
b = edist(two, test)
c = edist(one, two)
return (a**2 - b**2 + c**2) / (2 * c)
def closest(self, testCase):
return sorted([f for f in self.clusters],
key=lambda F: edist(F.exemplar(), testCase[:-1]))[0]
