Carlos-Francisco Méndez-Cruz / automatic-extraction-growth-conditions

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Estefani Gaytan Nunez
27e5966e 1 parent 5e66d15e

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Showing 2 changed files with 66 additions and 6 deletions
......@@ -79,7 +79,7 @@ if __name__ == '__main__':
print('------------------------------- SAVING DATA --------------------------------')
print('Saving score-table: ' + str(options.table))
imageName = os.path.join(options.outputPath, options.figureName)
savescreen(options.table, scores, imageName)
savescreen(options.table, scoresTable, imageName)
fig = plt.figure()
fig.set_figheight(13)
fig.set_figwidth(20)
......
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CV 0.8426343854107191 0.8375337951545059 0.8344412009392327 0.8342433957330186 0.8106324641347842 0.8200149039218473 0.8256738268677035 0.8222652765189232 0.8369330476694216 0.8324548394172087 0.8305332917162109 0.8269983740799899 0.8308032444965605 0.8337888246126737 0.8317218364725953 0.8295597513348965 0.8497587132907273 0.8514572032055473 0.8529397672009222 0.8530997523170145 0.8354648872990671 0.8438553480543364 0.833488403887471 0.8384402744923658 0.8504521104958047 0.856091701330711 0.8544270978232358 0.8512984764913196 0.818911081696952 0.8117042290979286 0.8211582395746769 0.8166537086281624 0.8263737544180966 0.8265144607685903 0.8266267801413506 0.8209562028933415 0.8153229850631285 0.8170382812294825 0.8214198138509978 0.8200873889763314 0.8200306160186037 0.8201549270256682 0.8172882049457899 0.8192294924716081 0.8315569437055503 0.826756700790382 0.823974602152804 0.830775030715119 0.8514396351676051 0.8443013668504182 0.8434032566660784 0.8577895989909314 0.8376625935961355 0.8381889879918965 0.8349604346257782 0.836408383376389 0.841060076118789 0.843848676674025 0.8426311049791738 0.8433941367984498 0.8189566663670631 0.8186349956286322 0.8193729864282642 0.8163619170548052
f1-score 0.805 0.809 0.804 0.811 0.816 0.802 0.812 0.808 0.816 0.814 0.810 0.804 0.815 0.815 0.817 0.817 0.821 0.820 0.818 0.815 0.817 0.823 0.817 0.814 0.818 0.813 0.823 0.820 0.807 0.801 0.812 0.806 0.804 0.811 0.804 0.806 0.832 0.815 0.808 0.813 0.809 0.801 0.804 0.801 0.814 0.818 0.815 0.817 0.813 0.816 0.815 0.814 0.815 0.813 0.811 0.821 0.816 0.818 0.818 0.823 0.812 0.799 0.807 0.803
precision 0.911 0.853 0.908 0.856 0.922 0.907 0.916 0.852 0.919 0.855 0.912 0.910 0.919 0.915 0.854 0.854 0.864 0.857 0.856 0.922 0.857 0.863 0.857 0.849 0.858 0.905 0.859 0.859 0.850 0.905 0.849 0.848 0.906 0.852 0.906 0.907 0.875 0.906 0.838 0.898 0.855 0.907 0.846 0.907 0.859 0.860 0.856 0.859 0.925 0.857 0.919 0.861 0.850 0.909 0.908 0.860 0.857 0.914 0.858 0.862 0.843 0.827 0.850 0.839
recall 0.746 0.777 0.746 0.781 0.760 0.742 0.750 0.773 0.752 0.783 0.752 0.742 0.754 0.758 0.787 0.787 0.789 0.789 0.787 0.752 0.785 0.791 0.785 0.785 0.785 0.756 0.793 0.789 0.773 0.742 0.781 0.773 0.746 0.779 0.746 0.748 0.802 0.767 0.785 0.764 0.773 0.740 0.771 0.740 0.779 0.785 0.783 0.783 0.750 0.783 0.754 0.777 0.787 0.758 0.756 0.789 0.783 0.760 0.785 0.791 0.787 0.779 0.773 0.773
CV f1-score precision recall
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