Hi guys I have this question because im trying to use ADTrees of weka on python using pyweka like this:
cls = Classifier(classname="weka.classifiers.trees.adtree", options=["-B", "10", "-E", "-3", "-S", "1"])
cls.build_classifier(data_modelos_1_2_csv)
but it reach this error:
Failed to instantiate weka.classifiers.trees.adtree: weka.classifiers.trees.adtree
Exception in thread "Thread-0" java.lang.ClassNotFoundException: weka.classifiers.trees.adtree
java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:581)
java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:178)
java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:522)
java.base/java.lang.Class.forName0(Native Method)
java.base/java.lang.Class.forName(Class.java:398)
weka.core.WekaPackageClassLoaderManager.forName(WekaPackageClassLoaderManager.java:198)
weka.core.WekaPackageClassLoaderManager.forName(WekaPackageClassLoaderManager.java:178)
weka.core.ResourceUtils.forName(ResourceUtils.java:80)
weka.core.Utils.forName(Utils.java:1112)
at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(BuiltinClassLoader.java:581)
at java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(ClassLoaders.java:178)
at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:522)
at java.base/java.lang.Class.forName0(Native Method)
at java.base/java.lang.Class.forName(Class.java:398)
at weka.core.WekaPackageClassLoaderManager.forName(WekaPackageClassLoaderManager.java:198)
at weka.core.WekaPackageClassLoaderManager.forName(WekaPackageClassLoaderManager.java:178)
at weka.core.ResourceUtils.forName(ResourceUtils.java:80)
at weka.core.Utils.forName(Utils.java:1112)
And this is the traceback:
AssertionError Traceback (most recent call last)
/tmp/ipykernel_6468/746392926.py in <module>
1 #from weka.classifiers import alternatingDecisionTrees
2
----> 3 cls = Classifier(classname="weka.classifiers.trees.adtree", options=["-B", "10", "-E", "-3", "-S", "1"])
4 cls.build_classifier(data_modelos_1_2_csv)
/usr/local/lib/python3.8/dist-packages/weka/classifiers.py in __init__(self, classname, jobject, options)
56 if jobject is None:
57 jobject = Classifier.new_instance(classname)
---> 58 self.enforce_type(jobject, "weka.classifiers.Classifier")
59 self.is_updateable = self.check_type(jobject, "weka.classifiers.UpdateableClassifier")
60 self.is_drawable = self.check_type(jobject, "weka.core.Drawable")
/usr/local/lib/python3.8/dist-packages/weka/core/classes.py in enforce_type(cls, jobject, intf_or_class)
867 :type intf_or_class: str
868 """
--> 869 if not cls.check_type(jobject, intf_or_class):
870 raise TypeError("Object does not implement or subclass " + intf_or_class + ": " + get_classname(jobject))
871
/usr/local/lib/python3.8/dist-packages/weka/core/classes.py in check_type(cls, jobject, intf_or_class)
855 :rtype: bool
856 """
--> 857 return is_instance_of(jobject, intf_or_class)
858
859 @classmethod
/usr/local/lib/python3.8/dist-packages/weka/core/classes.py in is_instance_of(obj, class_or_intf_name)
283 classname = get_classname(obj)
284 # array? retrieve component type and check that
--> 285 if is_array(obj):
286 jarray = JavaArray(jobject=obj)
287 classname = jarray.component_type()
/usr/local/lib/python3.8/dist-packages/weka/core/classes.py in is_array(obj)
307 :rtype: bool
308 """
--> 309 cls = javabridge.call(obj, "getClass", "()Ljava/lang/Class;")
310 return javabridge.call(cls, "isArray", "()Z")
311
~/.local/lib/python3.8/site-packages/javabridge/jutil.py in call(o, method_name, sig, *args)
886 '''
887 env = get_env()
--> 888 fn = make_call(o, method_name, sig)
889 args_sig = split_sig(sig[1:sig.find(')')])
890 ret_sig = sig[sig.find(')')+1:]
~/.local/lib/python3.8/site-packages/javabridge/jutil.py in make_call(o, method_name, sig)
834
835 '''
--> 836 assert o is not None
837 env = get_env()
838 if isinstance(o, basestring):
AssertionError:
So I don't know if exist any way to use this ADTrees on Python.
I tried with "weka.classifiers.trees.adtree", "weka.classifiers.trees.ADTree", using the imports
from weka.classifiers import alternatingDecisionTrees
from weka.classifiers import ADTree
from weka.classifiers import ADTrees
from weka.classifiers import adtree
from weka.classifiers import adtrees
Don't know what more to do.
python-weka-wrapper3, as the name suggests, is a light-weight wrapper around Weka classes. However, it mostly only wraps abstract superclasses, not all of the thousands of classes that make up Weka.
The weka.classifiers.Classifier class is the wrapper to use for classifiers and you need to specify the Java classname of the actual classifier that you want to wrap (in your case weka.classifiers.trees.ADTree). And, yes, just like Python, Java is also case sensitive.
Furthermore, if you require classes from packages, then you need to start the JVM with package support (default is no package support).
Below is an example that outputs the command-line of ADTree with its default parameters. If necessary, it installs the package first.
import sys
import weka.core.jvm as jvm
from weka.core.packages import is_installed, install_package
from weka.classifiers import Classifier
jvm.start(packages=True)
pkgname = "alternatingDecisionTrees"
if not is_installed(pkgname):
print("Package %s not installed, attempting installation..." % pkgname)
if install_package(pkgname):
print("Package %s installed, please rerun script!" % pkgname)
else:
print("Failed to install package %s!" % pkgname)
jvm.stop()
sys.exit(1)
cls = Classifier(classname="weka.classifiers.trees.ADTree", options=[])
print(cls.to_commandline())
jvm.stop()