trainer.set_null_flag("NULL")
modulepath = "pica.classifiers.%s"%(options.classification_algorithm)
classname = options.classification_algorithm.split(".")[-1]
ClassifierClass = __import__(modulepath, fromlist=(classname,))
classifier = ClassifierClass.__dict__[classname](options.parameters)
classifier.set_null_flag("NULL")
test_configurations = [TestConfiguration("A",None,trainer,classifier)]
#RVF changed (added the last 3 parameters)
if ( options.crossval_files ):
crossvalidator = CrossValidation(samples,options.parameters,options.folds,options.replicates,test_configurations,False,None,options.target_class,options.output_filename)
else:
crossvalidator = CrossValidation(samples,options.parameters,options.folds,options.replicates,test_configurations)
crossvalidator.crossvalidate()
classifications,misclassifications = crossvalidator.get_classification_vector()
metadata = None
if options.metadata:
metadata = fileio.load_metadata(options.metadata)
fout = open(options.output_filename,"w")
fout.write("who\t%s\tFalse Classifications\tTrue Classifications\tTotal"%(options.target_class))
if metadata:
for key in metadata.get_key_list():
fout.write("\t%s"%(key))
fout.write("\n")
for who in misclassifications.keys():
fout.write("%s\t%s\t%d\t%d\t%d"%(who,classes[who][options.target_class],misclassifications[who][0],misclassifications[who][1],misclassifications[who][0]+misclassifications[who][1]))
if metadata:
m = metadata.get(who,{})
