本文整理汇总了Python中disco.core.Job.params["nu"]方法的典型用法代码示例。如果您正苦于以下问题：Python Job.params["nu"]方法的具体用法？Python Job.params["nu"]怎么用？Python Job.params["nu"]使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类disco.core.Job的用法示例。
在下文中一共展示了Job.params["nu"]方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: fit
# 需要导入模块: from disco.core import Job [as 别名]
# 或者: from disco.core.Job import params["nu"] [as 别名]
def fit(dataset, nu=0.1, save_results=True, show=False):
"""
Function starts a job for calculation of model parameters
Parameters
----------
input - dataset object with input urls and other parameters
nu - parameter to adjust the classifier
save_results - save results to ddfs
show - show info about job execution
Returns
-------
Urls of fit model results on ddfs
"""
from disco.worker.pipeline.worker import Worker, Stage
from disco.core import Job
if dataset.params["y_map"] == []:
raise Exception("Linear proximal SVM requires a target label mapping parameter.")
try:
nu = float(nu)
if nu <= 0:
raise Exception("Parameter nu should be greater than 0")
except ValueError:
raise Exception("Parameter should be numerical.")
job = Job(worker=Worker(save_results=save_results))
# job parallelizes mappers and joins them with one reducer
job.pipeline = [
("split", Stage("map", input_chain=dataset.params["input_chain"], init=simple_init, process=map_fit)),
('group_all', Stage("reduce", init=simple_init, process=reduce_fit, combine=True))]
job.params = dataset.params
job.params["nu"] = nu
job.run(name="linearsvm_fit", input=dataset.params["data_tag"])
fitmodel_url = job.wait(show=show)
return {"linsvm_fitmodel": fitmodel_url} # return results url