def __init__(self, name, D = 2, kernel = "linear", alpha = 1.0, invert = False, kernel_params = {}, client = None):
params = {"D": D,
"kernel": kernel,
"alpha": alpha,
"invert": invert,
"kernel_params": kernel_params}
BasePipeline.__init__(self, name, "raw_kpca", client, params)
def run(self, model, matrix=None, matrix_name=None, matrix_type=None):
if matrix is not None:
return BasePipeline.run(self,
matrix_name=matrix.name,
matrix_type=matrix.type,
model=model)
else:
return BasePipeline.run(self,
matrix_name=matrix_name,
matrix_type=matrix_type,
model=model)
def __init__(self,
name,
kernel="linear",
alpha=1.0,
kernel_params={},
client=None):
params = {
"kernel": kernel,
"alpha": alpha,
"kernel_params": kernel_params
}
BasePipeline.__init__(self, name, "raw_krr", client, params)
def __init__(self,
name,
K=5,
kernel="euclidean",
algo="auto",
weights="uniform",
kernel_params={},
client=None):
params = {
"k": K,
"kernel": kernel,
"algo": algo,
"weights": weights,
"kernel_params": kernel_params
}
BasePipeline.__init__(self, name, "raw_knn_regressor", client, params)
def __init__(self,
name,
init_alpha=None,
init_beta=None,
trans_cov=None,
obs_cov=None,
init_cov=None,
optimizations=[],
client=None):
params = {
"init_alpha": init_alpha,
"init_beta": init_beta,
"trans_cov": trans_cov,
"obs_cov": obs_cov,
"init_cov": init_cov,
"optimizations": optimizations
}
BasePipeline.__init__(self, name, "kalman_ols", client, params)
def run(self, X, Y, model):
return BasePipeline.run(self, X=X, Y=Y, model=model)
def run(self, dataset, model):
return BasePipeline.run(self, dataset=dataset, model=model)
def __init__(self, name, corr_method="pearson", client=None):
params = {"corr_method": corr_method}
BasePipeline.__init__(self, name, "raw_mst", client, params)
def run(self, dataset, model, class_column):
return BasePipeline.run(self,
dataset=dataset,
model=model,
extra_params={"class_column": class_column})
def __init__(self, name, rate = 0.1, n_trees = 100, client = None):
params = {"rate" : min(0.5, rate),
"n_trees": n_trees}
BasePipeline.__init__(self, name, "isolation_forest", client, params)
def __init__(self, name, D=2, client=None):
params = {"D": D}
BasePipeline.__init__(self, name, "matrix_kpca", client, params)
def __init__(self, name, D = 2, K = 3, client = None):
params = {"D": D,
"K": K}
BasePipeline.__init__(self, name, "raw_isomap", client, params)
def __init__(self, name, D = 2, affinity = "knn", K = 5, gamma = 1.0, client = None):
params = {"D": D,
"K": K,
"affinity": affinity,
"gamma": gamma}
BasePipeline.__init__(self, name, "raw_laplacian_eigenmap", client, params)
def __init__(self, name, D = 2, K = 3, method = "standard", client = None):
params = {"D": D,
"k": K,
"method": method}
BasePipeline.__init__(self, name, "raw_lle", client, params)
def __init__(self, name, retrain = True, client = None):
params = {"retrain": retrain}
BasePipeline.__init__(self, name, "basic_a2d", client, params)
def __init__(self, name, bandwidth = "scott", client = None):
params = {"bandwidth": bandwidth}
BasePipeline.__init__(self, name, "raw_kde", client, params)
def __init__(self, name, alpha=0.1, client=None):
params = {"alpha": alpha}
BasePipeline.__init__(self, name, "matrix_agglomeration", client,
params)
def __init__(self, name, n_trees=8, client=None):
params = {
"n_trees": n_trees,
}
BasePipeline.__init__(self, name, "raw_rfr", client, params)
def __init__(self, name, kernel = "euclidean", geodesic = False, K = 5, kernel_params = {}, client = None):
params = {"k": K,
"kernel": kernel,
"kernel_params": kernel_params,
"geodesic": geodesic}
BasePipeline.__init__(self, name, "dist_matrix", client, params)
def __init__(self, name, K=3, client=None):
params = {"K": K}
BasePipeline.__init__(self, name, "raw_cfg", client, params)
def __init__(self, name, K=3, kernel="euclidean", client=None):
params = {"K": K, "kernel": kernel}
BasePipeline.__init__(self, name, "raw_knn_net", client, params)
def __init__(self, name, client=None):
params = {}
BasePipeline.__init__(self, name, "matrix_mst", client, params)
def __init__(self, name, sigma=0.1, client=None):
params = {"sigma": sigma}
BasePipeline.__init__(self, name, "raw_pnn", client, params)