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