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Week 2 - Pipeline CNN, eksperimen, laporan akhir

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2026-09-26 21:22:52 +07:00
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results/reports/classification_report_cnn.csv
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,precision,recall,f1-score,support
0,0.9938775510204082,0.9938775510204082,0.9938775510204082,980.0
1,0.992988606485539,0.9982378854625551,0.9956063268892794,1135.0
2,0.9932038834951457,0.9912790697674418,0.9922405431619786,1032.0
3,0.9940298507462687,0.9891089108910891,0.9915632754342432,1010.0
4,0.9908814589665653,0.9959266802443992,0.9933976637887253,982.0
5,0.9877232142857143,0.992152466367713,0.9899328859060402,892.0
6,0.9937304075235109,0.9926931106471816,0.9932114882506528,958.0
7,0.9893307468477207,0.9922178988326849,0.9907722195240408,1028.0
8,0.9836734693877551,0.9897330595482546,0.9866939611054247,974.0
9,0.9919436052366566,0.9762140733399405,0.984015984015984,1009.0
accuracy,0.9912,0.9912,0.9912,0.9912
macro avg,0.9911382793995284,0.9911440706121668,0.9911311899096779,10000.0
weighted avg,0.9912088120264272,0.9912,0.9911943463223446,10000.0
1 precision recall f1-score support
2 0 0.9938775510204082 0.9938775510204082 0.9938775510204082 980.0
3 1 0.992988606485539 0.9982378854625551 0.9956063268892794 1135.0
4 2 0.9932038834951457 0.9912790697674418 0.9922405431619786 1032.0
5 3 0.9940298507462687 0.9891089108910891 0.9915632754342432 1010.0
6 4 0.9908814589665653 0.9959266802443992 0.9933976637887253 982.0
7 5 0.9877232142857143 0.992152466367713 0.9899328859060402 892.0
8 6 0.9937304075235109 0.9926931106471816 0.9932114882506528 958.0
9 7 0.9893307468477207 0.9922178988326849 0.9907722195240408 1028.0
10 8 0.9836734693877551 0.9897330595482546 0.9866939611054247 974.0
11 9 0.9919436052366566 0.9762140733399405 0.984015984015984 1009.0
12 accuracy 0.9912 0.9912 0.9912 0.9912
13 macro avg 0.9911382793995284 0.9911440706121668 0.9911311899096779 10000.0
14 weighted avg 0.9912088120264272 0.9912 0.9911943463223446 10000.0