对样品数据进行K均值聚类的结果显示，编号为10 的样品为第类样品。（填写数字）/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif
举一反三
- K-中心聚类.sav 对这组样品进行K均值聚类，第三类中有个样品。（填写数字）/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif
- pm_customer_train二阶聚类.sav 新客户.sav根据第一组数据二阶聚类导出的模型，对新客户数据进行分类，新客户中编号为2的客户为第（）类客户。（填写数字）/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif
- pm_customer_train二阶聚类.sav 对客户数据进行二阶聚类，第二类客户人数为。填写数字/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif
- pm_customer_train二阶聚类.sav 对客户进行二阶聚类分析，采用系统自动确定类别数目，最后客户聚类数为。（填写数字）/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif
- Cluster_cars.sav 对上面数据进行系统聚类，那么聚类的对象是。（填写个案或者变量）/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif
内容
- 0
pm_customer_train二阶聚类.sav 对客户进行聚类分析，采用的距离测量方法是法。（填写汉字）/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif
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telco.sav 用神经网络模型对电信客户进行分类预测，编号为10的客户预测结果为第类客户。（填写数字）/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif
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价格涨幅校内校外有差异 PMIWYXY201810.sav PMIWYXY201811hx.sav PMIWYXY2018113+2.sav PMI国贸2班.sav PMI201812保险班.sav/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif/js/editor20150812/dialogs/attachment_new/fileTypeImages/icon_default.gif
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