def regression():
inp_dim, out_dim = 10, 5
params = {"max_depth": args.depth, "lr": args.lr, 'loss': b"mse"}
booster = GBDTMulti(LIB, out_dim=out_dim, params=params)
x_train, y_train = np.random.rand(10000, inp_dim), np.random.rand(10000, out_dim)
x_valid, y_valid = np.random.rand(10000, inp_dim), np.random.rand(10000, out_dim)
booster.set_data((x_train, y_train), (x_valid, y_valid))
booster.train(20)
booster.dump(b"regression.txt")
def classification():
inp_dim, out_dim = 10, 5
params = {"max_depth": args.depth, "lr": args.lr, 'loss': b"ce"}
booster = GBDTMulti(LIB, out_dim=out_dim, params=params)
x_train = np.random.rand(10000, inp_dim)
y_train = np.random.randint(0, out_dim, size=(10000, )).astype("int32")
x_valid = np.random.rand(10000, inp_dim)
y_valid = np.random.randint(0, out_dim, size=(10000, )).astype("int32")
booster.set_data((x_train, y_train), (x_valid, y_valid))
booster.train(20)
booster.dump(b"classification.txt")