小编rat*_*hna的帖子

我从声纳rest api获得了单元测试覆盖百分比指标.

如果构建低于定义值,如何使构建失败？

[WARNING] The POM for org.glassfish.jaxb:jaxb-runtime:jar:2.2.11 is invalid, 
 transitive dependencies (if any) will not be available, enable debug 
 logging for more
 details
[WARNING] The POM for org.glassfish.jaxb:jaxb-xjc:jar:2.2.11 is invalid, 
transitive dependencies (if any) will not be available, enable debug logging 
for more details
[WARNING] Error injecting: org.jvnet.mjiip.v_2.XJC2Mojo
 java.lang.NoClassDefFoundError: com/sun/codemodel/CodeWriter
    at java.base/java.lang.Class.getDeclaredConstructors0(Native Method)
    at java.base/java.lang.Class.privateGetDeclaredConstructors(Class.java:3110)
    at java.base/java.lang.Class.getDeclaredConstructors(Class.java:2314)
    at com.google.inject.spi.InjectionPoint.forConstructorOf(InjectionPoint.java:245)
    at com.google.inject.internal.ConstructorBindingImpl.create(ConstructorBindingImpl.java:99)
    at com.google.inject.internal.InjectorImpl.createUninitializedBinding(InjectorImpl.java:658)
    at com.google.inject.internal.InjectorImpl.createJustInTimeBinding(InjectorImpl.java:882)
    at com.google.inject.internal.InjectorImpl.createJustInTimeBindingRecursive(InjectorImpl.java:805)
    at com.google.inject.internal.InjectorImpl.getJustInTimeBinding(InjectorImpl.java:282)
    at com.google.inject.internal.InjectorImpl.getBindingOrThrow(InjectorImpl.java:214)
    at com.google.inject.internal.InjectorImpl.getProviderOrThrow(InjectorImpl.java:1006)
    at com.google.inject.internal.InjectorImpl.getProvider(InjectorImpl.java:1038)
    at com.google.inject.internal.InjectorImpl.getProvider(InjectorImpl.java:1001)
    at com.google.inject.internal.InjectorImpl.getInstance(InjectorImpl.java:1051)
    at org.eclipse.sisu.space.AbstractDeferredClass.get(AbstractDeferredClass.java:48)
    at …

我正在使用sklearn库来训练和测试我的数据。

targetDataCsv =  pd.read_csv("target.csv","rt"))
testNormalizedCsv = csv.reader(open("testdf_new.csv","rt",encoding="utf-8"))
traningNormalizedCsv = pd.read_csv("traindf_new.csv", skiprows=1,nrows=99999)
df = pd.read_csv("testdf_new.csv", skiprows=1, nrows=9999)

我想使用SGDClassifier的partial_fit方法，因为我的训练数据有超过200000行。

 X = traningNormalizedCsv.values
 y = targetDataCsv.values   
 clf = SGDClassifier()
 clf.partial_fit(X, y)

但是该分类器没有predict_proba方法来获取我的测试数据的目标概率。

   clf.predict_proba(df.values)

请提出建议。