Deep learning 如何使用OneHotencoding删除虚拟变量陷阱

以下是我的CSV数据提取和转换代码：

Schema schema = new Schema.Builder()
            .addColumnsString("RowNumber")
            .addColumnInteger("CustomerId")
            .addColumnString("Surname")
            .addColumnInteger("CreditScore")
            .addColumnCategorical("Geography",Arrays.asList("France","Spain","Germany"))
            .addColumnCategorical("Gender",Arrays.asList("Male","Female"))
            .addColumnsInteger("Age","Tenure","Balance","NumOfProducts","HasCrCard","IsActiveMember","EstimatedSalary","Exited").build();
    TransformProcess transformProcess = new TransformProcess.Builder(schema)
                                            .removeColumns("RowNumber","Surname","CustomerId")
                                            .categoricalToInteger("Gender")
                                            .categoricalToOneHot("Geography").build();
    RecordReader reader = new CSVRecordReader(1,',');
    reader.initialize(new FileSplit(new ClassPathResource("Churn_Modelling.csv").getFile()));
    TransformProcessRecordReader transformProcessRecordReader = new TransformProcessRecordReader(reader,transformProcess);
    System.out.println("args = " + transformProcessRecordReader.next() + "");

我刚试着打印第一张唱片：

args=[619,1,0,0,1,42,2,0,1,1,1,101348.88,1]

例如，三个值后跟619->1、0、0 我想保持619后面跟着0，0

基本上，我希望将第一个类别保留为基本类别，其他类别则从基本类别中预测，以避免任何多重共线关系（虚拟变量陷阱）

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我该怎么做？有人能给我一些建议吗

您可以使用

transformProcess.finalSchema

检查最终的转换模式，并使用

TransformProcess transformProcess = ... same as before...
        .categoricalToOneHot("Geography")
        .removeColumns("Geography[France]")
        .build()

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谢谢你，霍尔格。正是我要找的！