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23-05-29

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EBPSO 알고리즘 구현 - 선택지로 추가
random 으로 분산시키는 방법 구현 - 선택지로 추가
iris 기준 98퍼센트로 나오나 정확한 결과를 지켜봐야 할것으로 보임
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jung-geun
2023-05-29 04:01:48 +09:00
parent 7a612e4ca7
commit 91c6ec965b
27 changed files with 3378 additions and 1647 deletions
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2023-05-28 17:29:35,386 - pyswarms.single.global_best - INFO - Optimize for 20 iters with {'c1': 0.4, 'c2': 0.6, 'w': 0.4}
2023-05-28 17:30:07,637 - pyswarms.single.global_best - INFO - Optimization finished | best cost: 0.013333320617675781, best pos: [ 0.17027965 0.17696722 -0.07395054 0.31544984 0.17052408 -0.37810479
0.24267479 0.16931148 0.65606942 -0.24207116 -0.66562722 0.02191478
0.5870387 0.78966943 -0.4457816 0.0907434 -0.1808341 0.29282655
0.61472003 0.90660508 0.16469465 -0.55057763 0.54702005 -0.22636745
0.01125538 0.62431828 0.02128613 -0.26723577 -0.43527016 0.51223244
0.76388399 -0.02073011 0.15949622 0.45878514 0.01787211]
2023-05-28 17:30:08,140 - matplotlib.animation - WARNING - MovieWriter pillowwritter unavailable; using Pillow instead.
2023-05-28 17:30:08,141 - matplotlib.animation - INFO - Animation.save using <class 'matplotlib.animation.PillowWriter'>
2023-05-28 17:31:01,885 - tensorflow - WARNING - 5 out of the last 3010 calls to <function Model.make_test_function.<locals>.test_function at 0x7fee6622df70> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.
2023-05-28 17:31:08,794 - tensorflow - WARNING - 6 out of the last 3011 calls to <function Model.make_test_function.<locals>.test_function at 0x7fee66257b80> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.