kelompok3-deeplearning/results/02_cnn/reports/classification_report_cnn.csv

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