Kendall's Tau: 0.888Spearman's Rho: 0.982
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Neural Architecture Search
Neural architecture search (NAS) is a technique for automating the design of artificial neural networks (ANN), a widely used model in the field of machine learning. NAS essentially takes the process of a human manually tweaking a neural network and learning what works well, and automates this task to discover more complex architectures.
Image Credit : NAS with Reinforcement Learning
논문
Accuracy (Test): 46.71
Accuracy (%): 93.58%
Test Accuracy: 93.2Validation Accuracy: 0.844
Accuracy (Test): 46.54Accuracy (Val): 46.14
Kendall's Tau: 0.53Spearman's Rho: 0.73Pearson R: 0.72Acc. (test): 93.29
Accuracy (Test): 46.98Accuracy (Val): 46.51
Accuracy (Test): 46.38Search time (s): 151200
Test Accuracy: 93.23
Test Accuracy: 93.46
Accuracy (Test): 46.66Accuracy (Val): 46.16
Accuracy (Test): 46.36
Test Accuracy: 93.05
Specificity (VEB+): 95.04F1 score: 0.8929
Accuracy (Test): 46.42Accuracy (Val): 46.73
Test Accuracy: 93.55
Test Accuracy: 93.90
Accuracy (Test): 46.37Search time (s): 75600
Test Accuracy: 94.02
Test Accuracy: 94.13
Accuracy (Test): 46.85Accuracy (Val): 46.57
R2: 0.9314