阿里云人工智能平台PAIPS逻辑回归二分类-云淘科技

使用限制

PS逻辑回归二分类组件的输入数据需要满足以下要求：

• PS逻辑回归二分类组件的目标列仅支持数值类型，且0表示负例，1表示正例。如果MaxCompute表数据是STRING类型，则需要进行类型转换。例如，分类目标是Good/Bad字符串，需要转换为1/0。

• 如果数据是KV格式，则特征ID必须为正整数，特征值必须为实数。如果特征ID为字符串类型，则需要使用序列化组件进行序列化。如果特征值为类别型字符串，需要进行特征离散化等特征工程处理。

组件配置

您可以使用以下任意一种方式，配置PS逻辑回归二分类组件参数。

方式一：可视化方式

在Designer（原PAI-Studio）工作流页面配置组件参数。

方式二：PAI命令方式

使用PAI命令方式，配置该组件参数。您可以使用SQL脚本组件进行PAI命令调用，详情请参见SQL脚本。

#训练
PAI -name ps_lr
    -project algo_public
    -DinputTableName="lm_test_input"
    -DmodelName="logistic_regression_model"
    -DlabelColName="label"
    -DfeatureColNames="f0,f1,f2,f3,f4,f5"
    -Dl1Weight=1.0
    -Dl2Weight=0.0
    -DmaxIter=100
    -Depsilon=1e-6
    -DenableSparse=false
#预测
drop table if exists logistic_regression_predict;
PAI -name prediction
    -DmodelName="logistic_regression_model"
    -DoutputTableName="logistic_regression_predict"
    -DinputTableName="lm_test_input"
    -DappendColNames=label
    -DfeatureColNames="f0,f1,f2,f3,f4,f5"
    -DenableSparse=false

示例

1. 使用SQL语句，生成训练数据（以Dense格式数据为例）。

   drop table if exists lm_test_input;
   create table lm_test_input as
   select
   *
   from
   (
   select 0.72 as f0, 0.42 as f1, 0.55 as f2, -0.09 as f3, 1.79 as f4, -1.2 as f5, 0 as label from dual
   union all
   select 1.23 as f0, -0.33 as f1, -1.55 as f2, 0.92 as f3, -0.04 as f4, -0.1 as f5, 1 as label from dual
   union all
   select -0.2 as f0, -0.55 as f1, -1.28 as f2, 0.48 as f3, -1.7 as f4, 1.13 as f5, 1 as label from dual
   union all
   select 1.24 as f0, -0.68 as f1, 1.82 as f2, 1.57 as f3, 1.18 as f4, 0.2 as f5, 0 as label from dual
   union all
   select -0.85 as f0, 0.19 as f1, -0.06 as f2, -0.55 as f3, 0.31 as f4, 0.08 as f5, 1 as label from dual
   union all
   select 0.58 as f0, -1.39 as f1, 0.05 as f2, 2.18 as f3, -0.02 as f4, 1.71 as f5, 0 as label from dual
   union all
   select -0.48 as f0, 0.79 as f1, 2.52 as f2, -1.19 as f3, 0.9 as f4, -1.04 as f5, 1 as label from dual
   union all
   select 1.02 as f0, -0.88 as f1, 0.82 as f2, 1.82 as f3, 1.55 as f4, 0.53 as f5, 0 as label from dual
   union all
   select 1.19 as f0, -1.18 as f1, -1.1 as f2, 2.26 as f3, 1.22 as f4, 0.92 as f5, 0 as label from dual
   union all
   select -2.78 as f0, 2.33 as f1, 1.18 as f2, -4.5 as f3, -1.31 as f4, -1.8 as f5, 1 as label from dual
   ) tmp;

   生成的训练数据如下。

2. 构建如下实验，详情请参见算法建模。

3. 配置PS逻辑回归二分类组件的参数（配置如下表格中的参数，其余参数使用默认值）。

   页签	参数	描述
   字段设置	选择特征列	选择f0、f1、f2、f3、f4及f5列。
   	选择标签列	选择label列。
   执行调优	核心数	输入3。
   	每个核的内存大小	输入1024。

4. 配置预测组件的参数（配置如下表格中的参数，其余参数使用默认值）。

   页签	参数	描述
   字段设置	特征列	选择f0、f1、f2、f3、f4及f5列。
   	原样输出列	选择f0、f1、f2、f3、f4、f5及label列。

5. 运行实验，查看预测结果。其中prediction_detail列的1表示正例，0表示负例。