def __init__(self, result=global_var.ResultCluster()):
super(ClusterOut, self).__init__()
data = result.data
self.table = DataTable(data)
layout = QVBoxLayout()
layout.addWidget(self.table)
self.setLayout(layout)
def k_means_cluster(taskData):
"""
聚类
:param taskData:
:return:
"""
data = taskData.operateData.data # 操作数据
features = data.columns.tolist()
mdl = np.array(data[features])
K = global_var.currentTask.K
seed = 9
clf = KMeans(n_clusters=K, random_state=seed)
clf.fit(mdl)
data["label"] = clf.labels_ # 类别标记
result = global_var.ResultCluster()
result.model = clf
result.data = data
global_var.currentTask.result = result