The source code and dockerfile for the GSW2024 AI Lab.
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from sklearn.linear_model import LogisticRegression
from dtcontrol.benchmark_suite import BenchmarkSuite
from dtcontrol.decision_tree.decision_tree import DecisionTree
from dtcontrol.decision_tree.determinization.max_freq_determinizer import MaxFreqDeterminizer
from dtcontrol.decision_tree.impurity.entropy import Entropy
from dtcontrol.decision_tree.impurity.multi_label_entropy import MultiLabelEntropy
from dtcontrol.decision_tree.splitting.axis_aligned import AxisAlignedSplittingStrategy
from dtcontrol.decision_tree.splitting.linear_classifier import LinearClassifierSplittingStrategy
import pydot
def create_decision_tree(filename, name, output_folder,
timeout=60*60*2,
benchmark_file='benchmark',
save_folder='saved_classifiers',
export_pdf=False,
classifiers=None):
suite = BenchmarkSuite(timeout=timeout,
save_folder=save_folder,
output_folder=output_folder,
benchmark_file=benchmark_file,
rerun=True)
suite.add_datasets([filename])
if classifiers is None:
aa = AxisAlignedSplittingStrategy()
aa.priority = 1
classifiers = [DecisionTree([aa], Entropy(), name)]
suite.benchmark(classifiers)
if export_pdf:
for dataset in suite.datasets:
for classifier in classifiers:
filename = suite.get_filename(output_folder, dataset=dataset , classifier=classifier, extension='.dot')
(graph,) = pydot.graph_from_dot_file(filename)
graph.write_pdf(F'{name}.pdf')
return suite