def test_ValidationCorr_ReturnsConfusion(self):
X = self.makeh5(np.random.rand(10, 3))
T = self.makeh5(np.random.rand(10, 2))
hpelm = HPELM(3, 2, classification="c")
hpelm.add_neurons(6, "tanh")
fHH = self.makefile()
fHT = self.makefile()
hpelm.add_data(X, T, fHH=fHH, fHT=fHT)
_, _, confs = hpelm.validation_corr(fHH, fHT, X, T, steps=3)
self.assertGreater(np.sum(confs[0]), 1)
def test_ValidationCorr_ReturnsConfusion(self):
X = self.makeh5(np.random.rand(10, 3))
T = self.makeh5(np.random.rand(10, 2))
hpelm = HPELM(3, 2, classification="c")
hpelm.add_neurons(6, "tanh")
fHH = self.makefile()
fHT = self.makefile()
hpelm.add_data(X, T, fHH=fHH, fHT=fHT)
_, _, confs = hpelm.validation_corr(fHH, fHT, X, T, steps=3)
self.assertGreater(np.sum(confs[0]), 1)
def test_ValidationCorr_Works(self):
X = self.makeh5(np.random.rand(30, 3))
T = self.makeh5(np.random.rand(30, 2))
hpelm = HPELM(3, 2, norm=1e-6)
hpelm.add_neurons(6, "tanh")
fHH = self.makefile()
fHT = self.makefile()
hpelm.add_data(X, T, fHH=fHH, fHT=fHT)
nns, err, confs = hpelm.validation_corr(fHH, fHT, X, T, steps=3)
self.assertGreater(err[0], err[-1])
def test_ValidationCorr_Works(self):
X = self.makeh5(np.random.rand(30, 3))
T = self.makeh5(np.random.rand(30, 2))
hpelm = HPELM(3, 2, norm=1e-6)
hpelm.add_neurons(6, "tanh")
fHH = self.makefile()
fHT = self.makefile()
hpelm.add_data(X, T, fHH=fHH, fHT=fHT)
nns, err, confs = hpelm.validation_corr(fHH, fHT, X, T, steps=3)
self.assertGreater(err[0], err[-1])