參考文獻主要是[1][2]

[2]中代碼各種類函數都是自定義的,放棄吧

轉攻向[1]

------------------------------------------------------------------環境-------------------------------------------------------------------

組件	版本
Python	3.6.10
JDK	1.8.0_131

------------------------------------------------------------------準備工作------------------------------------------------------------------

pip install sklearn2pmml

python部分的代碼如下:

from sklearn2pmml import sklearn2pmml from sklearn2pmml.pipeline import PMMLPipeline from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression import numpy as np from sklearn import datasetsiris = datasets.load_iris() iris_data=iris['data'] iris_label=iris['target'] iris_target_name=iris['target_names'] X=np.array(iris_data) Y=np.array(iris_label)x_train, x_test, y_train, y_test = train_test_split(X, Y, train_size=0.85, random_state=1) model = PMMLPipeline([('LogisticModer', LogisticRegression(multi_class='ovr'))]) model.fit(x_train, y_train) y_hat = model.predict(x_test) loss = y_hat == y_test accuracy = np.mean(loss) print(accuracy) sklearn2pmml(model, './LogisticRegression.pmml', with_repr=True)

?

目前碰到了問題[3]無法解決

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Reference:

[1]sklearn2pmml安裝使用

[2]機器學習——Java調用sklearn生成好的Logistic模型進行鳶尾花的預測

[3]Exception in thread “main“ java.lang.IllegalArgumentException: http://www.dmg.org/PMML-4_4

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