def test_regression_not_supported(self): x = numpy.zeros((100, 10)) y = numpy.empty(dtype=[('event', bool), ('time', float)], shape=100) y['event'] = numpy.ones(100, dtype=bool) y['time'] = numpy.arange(100, dtype=float) ssvm = FastSurvivalSVM(rank_ratio=0, optimizer='simple') self.assertRaisesRegex(ValueError, "optimizer 'simple' does not implement regression objective", ssvm.fit, x, y) ssvm.set_params(optimizer='PRSVM') self.assertRaisesRegex(ValueError, "optimizer 'PRSVM' does not implement regression objective", ssvm.fit, x, y)
def test_regression_not_supported(self): x = numpy.zeros((100, 10)) y = numpy.empty(dtype=[('event', bool), ('time', float)], shape=100) y['event'] = numpy.ones(100, dtype=bool) y['time'] = numpy.arange(100, dtype=float) ssvm = FastSurvivalSVM(rank_ratio=0, optimizer='simple') self.assertRaisesRegex( ValueError, "optimizer 'simple' does not implement regression objective", ssvm.fit, x, y) ssvm.set_params(optimizer='PRSVM') self.assertRaisesRegex( ValueError, "optimizer 'PRSVM' does not implement regression objective", ssvm.fit, x, y)
def test_rank_ratio_out_of_bounds(self): x = numpy.zeros((100, 10)) y = numpy.empty(dtype=[('event', bool), ('time', float)], shape=100) y['event'] = numpy.ones(100, dtype=bool) y['time'] = numpy.arange(100, dtype=float) ssvm = FastSurvivalSVM(rank_ratio=-1) self.assertRaisesRegex(ValueError, "rank_ratio must be in \[0; 1\]", ssvm.fit, x, y) ssvm.set_params(rank_ratio=1.2) self.assertRaisesRegex(ValueError, "rank_ratio must be in \[0; 1\]", ssvm.fit, x, y) ssvm.set_params(rank_ratio=numpy.nan) self.assertRaisesRegex(ValueError, "rank_ratio must be in \[0; 1\]", ssvm.fit, x, y) ssvm.set_params(rank_ratio=numpy.inf) self.assertRaisesRegex(ValueError, "rank_ratio must be in \[0; 1\]", ssvm.fit, x, y)