140 lines
4.8 KiB
Python
140 lines
4.8 KiB
Python
import matplotlib.pyplot as pyplot
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import seaborn
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import pandas
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workspace = "/home/toshuumilia/Workspace/SML/" # Insert the working directory here.
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datasetPath = workspace + "data/sms.tsv" # Tells where is located the data
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# Experiment location
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# Graphs parameters
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globalFigsize = (12, 6)
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# Comparison Experiment #
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#
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# experimentOneDF = pandas.read_csv(experimentOnePath)
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#
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# seaborn.set_style("darkgrid")
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# pyplot.figure(figsize=globalFigsize)
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# seaborn.barplot(x="Value", y="Measure", hue="Method",
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# data=experimentOneDF)
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# pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
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# pyplot.ylabel('Measure', fontsize=12)
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# pyplot.xlabel('Value', fontsize=12)
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# pyplot.xlim(0.5, 1)
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# pyplot.title('Performance comparison between four learning methods', fontsize=15)
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# pyplot.show()
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# Decision Tree #
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# Depth Experiment
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#
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# experimentDTDepthDF = pandas.read_csv(workspace + "results/experimentDTDepth.csv")
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#
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# seaborn.set_style("whitegrid")
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# pyplot.figure(figsize=globalFigsize)
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# seaborn.barplot(x="Value", y="Measure", hue="Depth",
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# data=experimentDTDepthDF)
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# pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
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# pyplot.ylabel('Measure', fontsize=12)
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# pyplot.xlabel('Value', fontsize=12)
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# pyplot.xlim(0.5, 1)
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# pyplot.title('Performance comparison of a Decision Tree relative to a maximum depth', fontsize=15)
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# pyplot.show()
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# Criterion Experiment
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#
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# experimentDTCriterionDF = pandas.read_csv(workspace + "results/experimentDTCriterion.csv")
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#
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# seaborn.set_style("whitegrid")
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# pyplot.figure(figsize=globalFigsize)
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# seaborn.barplot(x="Value", y="Measure", hue="Criterion",
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# data=experimentDTCriterionDF)
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# pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
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# pyplot.ylabel('Measure', fontsize=12)
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# pyplot.xlabel('Value', fontsize=12)
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# pyplot.xlim(0.5, 1)
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# pyplot.title('Performance comparison of a Decision Tree relative to a splitting quality criterion', fontsize=15)
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# pyplot.show()
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# MinSampleSplit Experiment
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#
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# experimentDTMinSampleSplitDF = pandas.read_csv(workspace + "results/experimentDTMinSampleSplit.csv")
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#
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# seaborn.set_style("whitegrid")
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# pyplot.figure(figsize=globalFigsize)
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# seaborn.barplot(x="Value", y="Measure", hue="MinSampleSplit",
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# data=experimentDTMinSampleSplitDF)
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# pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
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# pyplot.ylabel('Measure', fontsize=12)
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# pyplot.xlabel('Value', fontsize=12)
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# pyplot.xlim(0.5, 1)
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# pyplot.title('Insert Title', fontsize=15)
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# pyplot.xticks(rotation='vertical')
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# pyplot.show()
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# MaxFeature Experiment
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#
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# experimentDTMaxFeatureDF = pandas.read_csv(workspace + "results/experimentDTMaxFeature.csv")
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#
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# seaborn.set_style("whitegrid")
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# pyplot.figure(figsize=globalFigsize)
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# seaborn.barplot(x="Value", y="Measure", hue="MaxFeature",
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# data=experimentDTMaxFeatureDF)
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# pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
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# pyplot.ylabel('Measure', fontsize=12)
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# pyplot.xlabel('Value', fontsize=12)
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# pyplot.xlim(0.5, 1)
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# pyplot.title('Insert Title', fontsize=15)
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# pyplot.xticks(rotation='vertical')
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# pyplot.show()
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# MaxLeafNodes Experiment
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# experimentDTMaxLeafNodesDF = pandas.read_csv(workspace + "results/experimentDTMaxLeafNodes.csv")
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#
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# seaborn.set_style("whitegrid")
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# pyplot.figure(figsize=globalFigsize)
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# seaborn.pointplot(y="Value", hue="Measure", x="MaxLeafNodes",
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# data=experimentDTMaxLeafNodesDF)
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# pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
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# pyplot.ylabel('Measure', fontsize=12)
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# pyplot.xlabel('Value', fontsize=12)
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# pyplot.xlim(0.5, 1)
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# pyplot.title('Insert Title', fontsize=15)
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# pyplot.xticks(rotation='vertical')
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# pyplot.show()
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# MinImpurityDecrease Experiment
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#
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# experimentDTMinImpurityDecreaseDF = pandas.read_csv(workspace + "results/experimentDTMinImpurityDecrease.csv")
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#
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# seaborn.set_style("whitegrid")
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# pyplot.figure(figsize=globalFigsize)
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# seaborn.pointplot(y="Value", hue="Measure", x="MinImpurityDecrease",
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# data=experimentDTMinImpurityDecreaseDF, palette="Greens_d")
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# pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
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# pyplot.ylabel('Measure Value', fontsize=12)
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# pyplot.xlabel('Min Impurity Decrease', fontsize=12)
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# pyplot.title('', fontsize=15)
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# pyplot.xticks(rotation='vertical')
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# pyplot.show()
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# BasicVsOptimized Experiment
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experimentDTBasicVsOptimizedDF = pandas.read_csv(workspace + "results/experimentDTBasicVsOptimized.csv")
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seaborn.set_style("whitegrid")
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pyplot.figure(figsize=globalFigsize)
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seaborn.barplot(x="Value", y="Measure", hue="Tuning",
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data=experimentDTBasicVsOptimizedDF)
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pyplot.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
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pyplot.ylabel('Measure', fontsize=12)
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pyplot.xlabel('Value', fontsize=12)
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pyplot.xlim(0.5, 1)
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pyplot.title('Insert Title', fontsize=15)
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pyplot.xticks(rotation='vertical')
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pyplot.show()
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