数据挖掘SPSSclementine培训PPT学习教案

1、会计学1数据挖掘数据挖掘SPSSclementine培训培训2第1页/共83页第2页/共83页4第3页/共83页5第4页/共83页6第5页/共83页7第6页/共83页8第7页/共83页9精炼模型未精炼模型第8页/共83页10决定一个数值或分类结果第9页/共83页11输出隐藏层输入层第10页/共83页12Cat.%nBad52.01168Good47.99155Total (100.00) 323Credit ranking (1=default)Cat.%nBad86.67143Good13.3322Total (51.08) 165Paid Weekly/MonthlyP-value=0.0

2、000, Chi-square=179.6665, df=1Weekly payCat.%nBad15.8225Good84.18133Total (48.92) 158Monthly salaryCat.%nBad90.51143Good9.4915Total (48.92) 158Age CategoricalP-value=0.0000, Chi-square=30.1113, df=1Young ( 35)Cat.%nBad48.9824Good51.0225Total (15.17) 49Age CategoricalP-value=0.0000, Chi-square=58.725

3、5, df=1Young ( 35)Cat.%nBad0.000Good 100.008Total(2.48)8Social ClassP-value=0.0016, Chi-square=12.0388, df=1Management;ClericalCat.%nBad58.5424Good41.4617Total (12.69) 41Professional第11页/共83页13第12页/共83页14第13页/共83页15第14页/共83页16第15页/共83页17第16页/共83页18第17页/共83页19第18页/共83页20和和第19页/共83页21第20页/共83页22第21页/共

4、83页23第22页/共83页24第23页/共83页25第24页/共83页26第25页/共83页27第26页/共83页28第27页/共83页29第28页/共83页30第29页/共83页31第30页/共83页32第31页/共83页33第32页/共83页34第33页/共83页35第34页/共83页36第35页/共83页37第36页/共83页38第37页/共83页39第38页/共83页40第39页/共83页41第40页/共83页42n保存更新的流第41页/共83页43第42页/共83页44第43页/共83页45第44页/共83页46第45页/共83页47第46页/共83页48第47页/共83页49第4

5、8页/共83页50第49页/共83页51第50页/共83页52第51页/共83页53第52页/共83页54第53页/共83页55第54页/共83页56第55页/共83页57第56页/共83页58第57页/共83页59第58页/共83页60第59页/共83页61第60页/共83页62第61页/共83页63第62页/共83页64第63页/共83页65第64页/共83页66第65页/共83页67第66页/共83页68第67页/共83页69第68页/共83页70第69页/共83页71n关联规则实例仅仅是相配前提的记录n序列规则实例相配整个规则的记录第70页/共83页72第71页/共83页73第72页/

6、共83页74第73页/共83页75第74页/共83页76第75页/共83页77 1. Perform many operations in the database.2. Perform the rest on a powerfulserver.3. Use the client processor for viewing results.4. Data isnt passedacross the networkunnecessarily.Data PreparationClementine FeaturesFull-process in-database mining with SQL op

7、timizationScalable performanceData PreparationClementine Features第76页/共83页78第77页/共83页79 CEMIClementine FeaturesNeed something else?Add new algorithms, data preparation, graphics, maps call other applications, etc even those that have been developed in-house第78页/共83页80 Clementine Stream ScriptNotes:F

8、or loop using in_fields.Loop applies to IN fields only.Train net node changes name so refer to it by type (theres only one).As usual, script “goes with” stream.# Start with empty palette.clear generated palette# Now loop through all IN fields and# train with each in turn set to NONE.# Give models appropriate names.for f in_fields_at typeif type.direction.f = INset type.direction.f = NONEset :name = omit_ fexecute :trainnetset