def main():
"""
Just runs some example code.
"""
# setup the flow
flow = Flow(name="list files")
listfiles = ListFiles()
listfiles.config["dir"] = str(helper.get_data_dir())
listfiles.config["list_files"] = True
listfiles.config["list_dirs"] = False
listfiles.config["recursive"] = False
listfiles.config["regexp"] = ".*.arff"
flow.actors.append(listfiles)
tee = Tee()
flow.actors.append(tee)
convert = Convert()
convert.config["setup"] = conversion.PassThrough()
tee.actors.append(convert)
console = Console()
console.config["prefix"] = "Match: "
tee.actors.append(console)
load = LoadDataset()
load.config["use_custom_loader"] = True
flow.actors.append(load)
cross = CrossValidate()
cross.config["setup"] = Classifier(classname="weka.classifiers.trees.J48",
options=["-C", "0.3"])
flow.actors.append(cross)
summary = EvaluationSummary()
summary.config["matrix"] = True
flow.actors.append(summary)
# print flow
flow.setup()
print("\n" + flow.tree + "\n")
# save the flow
fname = tempfile.gettempdir() + os.sep + "simpleflow.json"
Flow.save(flow, fname)
# load flow
fl2 = Flow.load(fname)
# output flow
fl2.setup()
print("\n" + fl2.tree + "\n")
def main():
"""
Just runs some example code.
"""
# setup the flow
helper.print_title("Output actor help")
cv = CrossValidate()
cv.config["setup"] = Classifier(classname="weka.classifiers.trees.J48")
cv.print_help()
def main():
"""
Just runs some example code.
"""
# setup the flow
flow = Flow(name="list files")
listfiles = ListFiles()
listfiles.config["dir"] = str(helper.get_data_dir())
listfiles.config["list_files"] = True
listfiles.config["list_dirs"] = False
listfiles.config["recursive"] = False
listfiles.config["regexp"] = ".*.arff"
flow.actors.append(listfiles)
tee = Tee()
flow.actors.append(tee)
convert = Convert()
convert.config["setup"] = conversion.PassThrough()
tee.actors.append(convert)
console = Console()
console.config["prefix"] = "Match: "
tee.actors.append(console)
load = LoadDataset()
load.config["use_custom_loader"] = True
flow.actors.append(load)
cross = CrossValidate()
cross.config["setup"] = Classifier(classname="weka.classifiers.trees.J48", options=["-C", "0.3"])
flow.actors.append(cross)
summary = EvaluationSummary()
summary.config["matrix"] = True
flow.actors.append(summary)
# print flow
flow.setup()
print("\n" + flow.tree + "\n")
# save the flow
fname = tempfile.gettempdir() + os.sep + "simpleflow.json"
Flow.save(flow, fname)
# load flow
fl2 = Flow.load(fname)
# output flow
fl2.setup()
print("\n" + fl2.tree + "\n")
def main():
"""
Just runs some example code.
"""
# setup the flow
helper.print_title("Cross-validate clusterer")
iris = helper.get_data_dir() + os.sep + "iris.arff"
flow = Flow(name="cross-validate clusterer")
filesupplier = FileSupplier()
filesupplier.config["files"] = [iris]
flow.actors.append(filesupplier)
loaddataset = LoadDataset()
flow.actors.append(loaddataset)
flter = Filter()
flter.name = "Remove class"
flter.config["filter"] = filters.Filter(
classname="weka.filters.unsupervised.attribute.Remove",
options=["-R", "last"])
flow.actors.append(flter)
cv = CrossValidate()
cv.config["setup"] = Clusterer(classname="weka.clusterers.EM")
flow.actors.append(cv)
console = Console()
console.config["prefix"] = "Loglikelihood: "
flow.actors.append(console)
# run the flow
msg = flow.setup()
if msg is None:
print("\n" + flow.tree + "\n")
msg = flow.execute()
if msg is not None:
print("Error executing flow:\n" + msg)
else:
print("Error setting up flow:\n" + msg)
flow.wrapup()
flow.cleanup()
def main():
"""
Just runs some example code.
"""
# setup the flow
helper.print_title("Cross-validate clusterer")
iris = helper.get_data_dir() + os.sep + "iris.arff"
flow = Flow(name="cross-validate clusterer")
filesupplier = FileSupplier()
filesupplier.config["files"] = [iris]
flow.actors.append(filesupplier)
loaddataset = LoadDataset()
flow.actors.append(loaddataset)
flter = Filter()
flter.name = "Remove class"
flter.config["filter"] = filters.Filter(
classname="weka.filters.unsupervised.attribute.Remove", options=["-R", "last"])
flow.actors.append(flter)
cv = CrossValidate()
cv.config["setup"] = Clusterer(classname="weka.clusterers.EM")
flow.actors.append(cv)
console = Console()
console.config["prefix"] = "Loglikelihood: "
flow.actors.append(console)
# run the flow
msg = flow.setup()
if msg is None:
print("\n" + flow.tree + "\n")
msg = flow.execute()
if msg is not None:
print("Error executing flow:\n" + msg)
else:
print("Error setting up flow:\n" + msg)
flow.wrapup()
flow.cleanup()
def main():
"""
Just runs some example code.
"""
# setup the flow
helper.print_title("Cross-validate classifier")
iris = helper.get_data_dir() + os.sep + "iris.arff"
flow = Flow(name="cross-validate classifier")
filesupplier = FileSupplier()
filesupplier.config["files"] = [iris]
flow.actors.append(filesupplier)
loaddataset = LoadDataset()
flow.actors.append(loaddataset)
select = ClassSelector()
select.config["index"] = "last"
flow.actors.append(select)
cv = CrossValidate()
cv.config["setup"] = Classifier(classname="weka.classifiers.trees.J48")
flow.actors.append(cv)
branch = Branch()
flow.actors.append(branch)
seqsum = Sequence()
seqsum.name = "summary"
branch.actors.append(seqsum)
summary = EvaluationSummary()
summary.config["title"] = "=== J48/iris ==="
summary.config["complexity"] = False
summary.config["matrix"] = True
seqsum.actors.append(summary)
console = Console()
seqsum.actors.append(console)
seqerr = Sequence()
seqerr.name = "errors"
branch.actors.append(seqerr)
errors = ClassifierErrors()
errors.config["wait"] = False
seqerr.actors.append(errors)
seqroc = Sequence()
seqroc.name = "roc"
branch.actors.append(seqroc)
roc = ROC()
roc.config["wait"] = False
roc.config["class_index"] = [0, 1, 2]
seqroc.actors.append(roc)
seqprc = Sequence()
seqprc.name = "prc"
branch.actors.append(seqprc)
prc = PRC()
prc.config["wait"] = True
prc.config["class_index"] = [0, 1, 2]
seqprc.actors.append(prc)
# run the flow
msg = flow.setup()
if msg is None:
print("\n" + flow.tree + "\n")
msg = flow.execute()
if msg is not None:
print("Error executing flow:\n" + msg)
else:
print("Error setting up flow:\n" + msg)
flow.wrapup()
flow.cleanup()
