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加入实验输出（批次 11/14）

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gloamxun
2026-09-23 23:36:24 +08:00
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deep_learning/Q1/outputs/method_comparison/comparison_summary.csv
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method,mvr_text,entropy_text,trajectory_span_text,mvr_audio,entropy_audio,trajectory_span_audio,mvr_vision,entropy_vision,trajectory_span_vision,r_at_1_text_to_audio,r_at_5_text_to_audio,r_at_1_text_to_vision,r_at_5_text_to_vision,reconstruction_mae_text,reconstruction_mae_audio,reconstruction_mae_vision,emotion_accuracy,emotion_macro_f1,emotion_mae,emotion_pearson
M1,0.0,0.0008249471336603165,0.8612861529795919,0.0,0.35824004098773005,0.8937758523714728,0.0,0.02091189981205389,0.8956127409730107,0.0012000000569969416,0.007000000309199094,0.0020000000949949026,0.007000000402331352,0.8308010935783386,0.6908806562423706,0.9209612965583801,0.5900000000000001,0.43700352733686065,0.5521364179253578,0.5305163430956757
M2,0.0,0.003971234038472176,0.8611038638930768,0.0,0.39199826538562776,0.968455815287307,0.0,0.015714890849776567,0.9744537002407014,0.0014000000432133675,0.009200000390410423,0.003600000194273889,0.008800000487826764,0.8190697312355042,0.6621044635772705,0.9195392370223999,0.55,0.3434301254301254,0.5691992919147014,0.5082439027512137
M3,0.0,0.0004981429129838944,0.8611844960658346,0.01857142824679613,0.992265993754069,-0.001562372346719104,0.06843537279715141,0.9827406370639801,-0.004611149926980335,0.01966666733690848,0.043000001646578315,0.0062666668944681685,0.013800000709791978,0.8311106324195862,0.38449583053588865,0.868217929204305,0.5766666666666667,0.43789820467598245,0.5534388141334057,0.5457241196963684
M4,0.0,0.9999777108430863,0.00020046850045522113,0.0,0.9999900078773498,4.607309897740703e-05,0.0,0.9999960112571716,0.00010548800230026034,0.007066666963510215,0.01226666709408164,0.0016000000604738792,0.00760000046963493,0.4924671709537506,0.37839911778767904,0.8630666335423788,0.56,0.41446068467573843,0.6231901267170906,0.5067829543507287
1 method mvr_text entropy_text trajectory_span_text mvr_audio entropy_audio trajectory_span_audio mvr_vision entropy_vision trajectory_span_vision r_at_1_text_to_audio r_at_5_text_to_audio r_at_1_text_to_vision r_at_5_text_to_vision reconstruction_mae_text reconstruction_mae_audio reconstruction_mae_vision emotion_accuracy emotion_macro_f1 emotion_mae emotion_pearson
2 M1 0.0 0.0008249471336603165 0.8612861529795919 0.0 0.35824004098773005 0.8937758523714728 0.0 0.02091189981205389 0.8956127409730107 0.0012000000569969416 0.007000000309199094 0.0020000000949949026 0.007000000402331352 0.8308010935783386 0.6908806562423706 0.9209612965583801 0.5900000000000001 0.43700352733686065 0.5521364179253578 0.5305163430956757
3 M2 0.0 0.003971234038472176 0.8611038638930768 0.0 0.39199826538562776 0.968455815287307 0.0 0.015714890849776567 0.9744537002407014 0.0014000000432133675 0.009200000390410423 0.003600000194273889 0.008800000487826764 0.8190697312355042 0.6621044635772705 0.9195392370223999 0.55 0.3434301254301254 0.5691992919147014 0.5082439027512137
4 M3 0.0 0.0004981429129838944 0.8611844960658346 0.01857142824679613 0.992265993754069 -0.001562372346719104 0.06843537279715141 0.9827406370639801 -0.004611149926980335 0.01966666733690848 0.043000001646578315 0.0062666668944681685 0.013800000709791978 0.8311106324195862 0.38449583053588865 0.868217929204305 0.5766666666666667 0.43789820467598245 0.5534388141334057 0.5457241196963684
5 M4 0.0 0.9999777108430863 0.00020046850045522113 0.0 0.9999900078773498 4.607309897740703e-05 0.0 0.9999960112571716 0.00010548800230026034 0.007066666963510215 0.01226666709408164 0.0016000000604738792 0.00760000046963493 0.4924671709537506 0.37839911778767904 0.8630666335423788 0.56 0.41446068467573843 0.6231901267170906 0.5067829543507287