def main():
X1, X2, Y = davis_data.load_davis()
Y = Y.ravel(order='F')
learner = KronRLS(X1 = X1, X2 = X2, Y = Y)
log_regparams = range(15, 35)
for log_regparam in log_regparams:
learner.solve(2.**log_regparam)
P = learner.in_sample_loo()
perf = cindex(Y, P)
print("regparam 2**%d, cindex %f" %(log_regparam, perf))
def main():
X1, X2, Y = davis_data.load_davis()
Y = Y.ravel(order='F')
learner = TwoStepRLS(X1 = X1, X2 = X2, Y = Y, regparam1=1.0, regparam2=1.0)
log_regparams1 = range(-8, -4)
log_regparams2 = range(20,25)
for log_regparam1 in log_regparams1:
for log_regparam2 in log_regparams2:
learner.solve(2.**log_regparam1, 2.**log_regparam2)
P = learner.in_sample_loo()
perf = cindex(Y, P)
print("regparam 2**%d 2**%d, cindex %f" %(log_regparam1, log_regparam2, perf))
def main():
X1, X2, Y = davis_data.load_davis()
Y = Y.ravel(order='F')
learner = TwoStepRLS(X1=X1, X2=X2, Y=Y, regparam1=1.0, regparam2=1.0)
log_regparams1 = range(-8, -4)
log_regparams2 = range(20, 25)
for log_regparam1 in log_regparams1:
for log_regparam2 in log_regparams2:
learner.solve(2.**log_regparam1, 2.**log_regparam2)
P = learner.in_sample_loo()
perf = cindex(Y, P)
print("regparam 2**%d 2**%d, cindex %f" %
(log_regparam1, log_regparam2, perf))
def main():
X1, X2, Y = davis_data.load_davis()
n = X1.shape[0]
m = X2.shape[0]
Y = Y.ravel(order='F')
learner = TwoStepRLS(X1 = X1, X2 = X2, Y = Y, regparam1=1.0, regparam2=1.0)
log_regparams1 = range(-8, -4)
log_regparams2 = range(20,25)
#Create random split to 5 folds for the drug-target pairs
folds = random_folds(n*m, 5, seed=12345)
#Map the indices back to (drug_indices, target_indices)
folds = [np.unravel_index(fold, (n,m)) for fold in folds]
for log_regparam1 in log_regparams1:
for log_regparam2 in log_regparams2:
learner.solve(2.**log_regparam1, 2.**log_regparam2)
P = learner.in_sample_kfoldcv(folds)
perf = cindex(Y, P)
print("regparam 2**%d 2**%d, cindex %f" %(log_regparam1, log_regparam2, perf))
def main():
X1, X2, Y = davis_data.load_davis()
n = X1.shape[0]
m = X2.shape[0]
Y = Y.ravel(order='F')
learner = TwoStepRLS(X1=X1, X2=X2, Y=Y, regparam1=1.0, regparam2=1.0)
log_regparams1 = range(-8, -4)
log_regparams2 = range(20, 25)
#Create random split to 5 folds for the drug-target pairs
folds = random_folds(n * m, 5, seed=12345)
#Map the indices back to (drug_indices, target_indices)
folds = [np.unravel_index(fold, (n, m)) for fold in folds]
for log_regparam1 in log_regparams1:
for log_regparam2 in log_regparams2:
learner.solve(2.**log_regparam1, 2.**log_regparam2)
P = learner.in_sample_kfoldcv(folds)
perf = cindex(Y, P)
print("regparam 2**%d 2**%d, cindex %f" %
(log_regparam1, log_regparam2, perf))
