首页
学习
活动
专区
圈层
工具
发布
首页
学习
活动
专区
圈层
工具
MCP广场
社区首页 >问答首页 >无法创建PMML,因为未指定输入要素的数量

无法创建PMML,因为未指定输入要素的数量
EN

Stack Overflow用户
提问于 2020-05-25 15:48:50
回答 1查看 150关注 0票数 0

我无法将以下管道转换为pmml,因为“未指定输入特征的数量”。

重现错误的最小示例管道是:

代码语言:javascript
运行
复制
import pandas as pd
from sklearn.compose import ColumnTransformer
from sklearn.ensemble import RandomForestRegressor
from sklearn.model_selection import train_test_split
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler, OneHotEncoder
from sklearn2pmml import sklearn2pmml
from sklearn2pmml.pipeline import PMMLPipeline

if __name__ == '__main__':

    data_dict = {
        'age': [1, 2, 3],
        'day_of_week': ['monday', 'tuesday', 'wednesday'],
        'y': [5, 6, 7]
    }

    data = pd.DataFrame(data_dict, columns=data_dict)

    numeric_features = ['age']
    numeric_transformer = Pipeline(steps=[
        ('scaler', StandardScaler())])

    categorical_features = ['day_of_week']
    categorical_transformer = Pipeline(steps=[
        ('onehot', OneHotEncoder(handle_unknown='ignore', categories='auto'))])

    preprocessor = ColumnTransformer(
        transformers=[
            ('numerical', numeric_transformer, numeric_features),
            ('categorical', categorical_transformer, categorical_features)])

    pipeline = Pipeline(
        steps=[
            ('preprocessor', preprocessor),
            ('classifier', RandomForestRegressor(n_estimators=60))])

    X = data.drop(labels=['y'], axis=1)
    y = data['y']

    X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.8, random_state=30)

    trained_model = pipeline.fit(X=X_train, y=y_train)

    pmml_pipeline = PMMLPipeline([
        ("pipeline", pipeline)
    ])

    sklearn2pmml(pipeline=pmml_pipeline, pmml='RandomForestRegressor2.pmml', with_repr=True)

我从sklearn2pmml得到的Java错误消息是:

代码语言:javascript
运行
复制
Standard output is empty
Standard error:
May 25, 2020 9:37:56 AM org.jpmml.sklearn.Main run
INFO: Parsing PKL..
May 25, 2020 9:38:07 AM org.jpmml.sklearn.Main run
INFO: Parsed PKL in 11453 ms.
May 25, 2020 9:38:07 AM org.jpmml.sklearn.Main run
INFO: Converting..
May 25, 2020 9:38:07 AM sklearn2pmml.pipeline.PMMLPipeline initTargetFields
WARNING: Attribute 'sklearn2pmml.pipeline.PMMLPipeline.target_fields' is not set. Assuming y as the name of the target field
May 25, 2020 9:38:07 AM org.jpmml.sklearn.Main run
SEVERE: Failed to convert
java.lang.IllegalArgumentException: The transformer object of the first step (Python class sklearn.pipeline.Pipeline) does not specify the number of input features
    at sklearn2pmml.pipeline.PMMLPipeline.initActiveFields(PMMLPipeline.java:522)
    at sklearn2pmml.pipeline.PMMLPipeline.encodePMML(PMMLPipeline.java:214)
    at org.jpmml.sklearn.Main.run(Main.java:228)
    at org.jpmml.sklearn.Main.main(Main.java:148)

Exception in thread "main" java.lang.IllegalArgumentException: The transformer object of the first step (Python class sklearn.pipeline.Pipeline) does not specify the number of input features
    at sklearn2pmml.pipeline.PMMLPipeline.initActiveFields(PMMLPipeline.java:522)
    at sklearn2pmml.pipeline.PMMLPipeline.encodePMML(PMMLPipeline.java:214)
    at org.jpmml.sklearn.Main.run(Main.java:228)
    at org.jpmml.sklearn.Main.main(Main.java:148)


Process finished with exit code 1
EN

回答 1

Stack Overflow用户

回答已采纳

发布于 2020-05-25 15:56:26

基于sklearn.pipeline.Pipeline创建单步sklearn2pmml.pipline.PMMLPipeline有什么意义

省略这个no-op,转换应该会成功:

代码语言:javascript
运行
复制
pipeline = PMMLPipeline(
    steps=[
        ('preprocessor', preprocessor),
        ('classifier', RandomForestRegressor(n_estimators=60))])
pipeline.fit(X=X_train, y=y_train)
sklearn2pmml(pipeline, "RandomForestRegressor2.pmml")
票数 1
EN
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接:

https://stackoverflow.com/questions/61997983

复制
相关文章

相似问题

领券
问题归档专栏文章快讯文章归档关键词归档开发者手册归档开发者手册 Section 归档