def main():
"""
Just runs some example code.
"""
# setup the flow
helper.print_title("build and evaluate classifier")
iris = helper.get_data_dir() + os.sep + "iris.arff"
flow = Flow(name="build and evaluate classifier")
start = Start()
flow.actors.append(start)
build_save = Trigger()
build_save.name = "build and store classifier"
flow.actors.append(build_save)
filesupplier = FileSupplier()
filesupplier.config["files"] = [iris]
build_save.actors.append(filesupplier)
loaddataset = LoadDataset()
build_save.actors.append(loaddataset)
select = ClassSelector()
select.config["index"] = "last"
build_save.actors.append(select)
ssv = SetStorageValue()
ssv.config["storage_name"] = "data"
build_save.actors.append(ssv)
train = Train()
train.config["setup"] = Classifier(classname="weka.classifiers.trees.J48")
build_save.actors.append(train)
pick = ContainerValuePicker()
pick.config["value"] = "Model"
build_save.actors.append(pick)
ssv = SetStorageValue()
ssv.config["storage_name"] = "model"
pick.actors.append(ssv)
evaluate = Trigger()
evaluate.name = "evaluate classifier"
flow.actors.append(evaluate)
gsv = GetStorageValue()
gsv.config["storage_name"] = "data"
evaluate.actors.append(gsv)
evl = Evaluate()
evl.config["storage_name"] = "model"
evaluate.actors.append(evl)
summary = EvaluationSummary()
summary.config["matrix"] = True
evaluate.actors.append(summary)
console = Console()
evaluate.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("build and evaluate classifier")
iris = helper.get_data_dir() + os.sep + "iris.arff"
flow = Flow(name="build and evaluate classifier")
start = Start()
flow.actors.append(start)
build_save = Trigger()
build_save.name = "build and store classifier"
flow.actors.append(build_save)
filesupplier = FileSupplier()
filesupplier.config["files"] = [iris]
build_save.actors.append(filesupplier)
loaddataset = LoadDataset()
build_save.actors.append(loaddataset)
select = ClassSelector()
select.config["index"] = "last"
build_save.actors.append(select)
ssv = SetStorageValue()
ssv.config["storage_name"] = "data"
build_save.actors.append(ssv)
train = Train()
train.config["setup"] = Classifier(classname="weka.classifiers.trees.J48")
build_save.actors.append(train)
pick = ContainerValuePicker()
pick.config["value"] = "Model"
build_save.actors.append(pick)
ssv = SetStorageValue()
ssv.config["storage_name"] = "model"
pick.actors.append(ssv)
evaluate = Trigger()
evaluate.name = "evaluate classifier"
flow.actors.append(evaluate)
gsv = GetStorageValue()
gsv.config["storage_name"] = "data"
evaluate.actors.append(gsv)
evl = Evaluate()
evl.config["storage_name"] = "model"
evaluate.actors.append(evl)
summary = EvaluationSummary()
summary.config["matrix"] = True
evaluate.actors.append(summary)
console = Console()
evaluate.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
count = 50
helper.print_title("build clusterer incrementally")
iris = helper.get_data_dir() + os.sep + "iris.arff"
flow = Flow(name="build clusterer incrementally")
filesupplier = FileSupplier()
filesupplier.config["files"] = [iris]
flow.actors.append(filesupplier)
initcounter = InitStorageValue()
initcounter.config["storage_name"] = "counter"
initcounter.config["value"] = 0
flow.actors.append(initcounter)
loaddataset = LoadDataset()
loaddataset.config["incremental"] = True
flow.actors.append(loaddataset)
remove = Filter(name="remove class attribute")
remove.config["setup"] = filters.Filter(
classname="weka.filters.unsupervised.attribute.Remove",
options=["-R", "last"])
flow.actors.append(remove)
inccounter = UpdateStorageValue()
inccounter.config["storage_name"] = "counter"
inccounter.config["expression"] = "{X} + 1"
flow.actors.append(inccounter)
train = Train()
train.config["setup"] = Clusterer(classname="weka.clusterers.Cobweb")
flow.actors.append(train)
pick = ContainerValuePicker()
pick.config["value"] = "Model"
pick.config["switch"] = True
flow.actors.append(pick)
tee = Tee(name="output model every " + str(count) + " instances")
tee.config["condition"] = "@{counter} % " + str(count) + " == 0"
flow.actors.append(tee)
trigger = Trigger(name="output # of instances")
tee.actors.append(trigger)
getcounter = GetStorageValue()
getcounter.config["storage_name"] = "counter"
trigger.actors.append(getcounter)
console = Console()
console.config["prefix"] = "# of instances: "
trigger.actors.append(console)
console = Console(name="output model")
tee.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
count = 50
helper.print_title("build classifier incrementally")
iris = helper.get_data_dir() + os.sep + "iris.arff"
flow = Flow(name="build classifier incrementally")
filesupplier = FileSupplier()
filesupplier.config["files"] = [iris]
flow.actors.append(filesupplier)
initcounter = InitStorageValue()
initcounter.config["storage_name"] = "counter"
initcounter.config["value"] = 0
flow.actors.append(initcounter)
loaddataset = LoadDataset()
loaddataset.config["incremental"] = True
flow.actors.append(loaddataset)
select = ClassSelector()
select.config["index"] = "last"
flow.actors.append(select)
inccounter = UpdateStorageValue()
inccounter.config["storage_name"] = "counter"
inccounter.config["expression"] = "{X} + 1"
flow.actors.append(inccounter)
train = Train()
train.config["setup"] = Classifier(classname="weka.classifiers.bayes.NaiveBayesUpdateable")
flow.actors.append(train)
pick = ContainerValuePicker()
pick.config["value"] = "Model"
pick.config["switch"] = True
flow.actors.append(pick)
tee = Tee(name="output model every " + str(count) + " instances")
tee.config["condition"] = "@{counter} % " + str(count) + " == 0"
flow.actors.append(tee)
trigger = Trigger(name="output # of instances")
tee.actors.append(trigger)
getcounter = GetStorageValue()
getcounter.config["storage_name"] = "counter"
trigger.actors.append(getcounter)
console = Console()
console.config["prefix"] = "# of instances: "
trigger.actors.append(console)
console = Console(name="output model")
tee.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()
