def __init__(self):
super(LocalBaseline, self).__init__()
self.model_param = LocalBaselineParam()
self.model_name = "LocalBaseline"
self.metric_type = ""
self.model_param_name = "LocalBaselineParam"
self.model_meta_name = "LocalBaselineMeta"
def __init__(self):
super(LocalBaseline, self).__init__()
self.model_param = LocalBaselineParam()
self.model_name = "LocalBaseline"
self.metric_type = ""
self.model_param_name = "LocalBaselineParam"
self.model_meta_name = "LocalBaselineMeta"
# one_ve_rest parameter
self.need_one_vs_rest = None
self.one_vs_rest_classes = []
self.one_vs_rest_obj = None
def setUp(self):
self.job_id = str(uuid.uuid1())
session.init("test_random_sampler_" + self.job_id)
data_num = 100
feature_num = 8
self.prepare_data(data_num, feature_num)
params = LocalBaselineParam()
local_baseline_obj = LocalBaseline()
local_baseline_obj._init_model(params)
local_baseline_obj.need_run = True
local_baseline_obj.header = ["x1", "x2", "x3", "x4", "x5", "x6", "x7", "x8"]
local_baseline_obj.model_name = "LogisticRegression"
local_baseline_obj.model_opts = {}
self.local_baseline_obj = local_baseline_obj
def setUp(self):
self.job_id = str(uuid.uuid1())
self.session = Session.create(0,
0).init_computing(self.job_id).computing
data_num = 100
feature_num = 8
self.prepare_data(data_num, feature_num)
params = LocalBaselineParam()
local_baseline_obj = LocalBaseline()
local_baseline_obj._init_model(params)
local_baseline_obj.need_run = True
local_baseline_obj.header = [
"x1", "x2", "x3", "x4", "x5", "x6", "x7", "x8"
]
local_baseline_obj.model_name = "LogisticRegression"
local_baseline_obj.model_opts = {}
self.local_baseline_obj = local_baseline_obj