AI4 Retina image 보호되어 있는 글 입니다. 2023. 6. 4. Sensitivity analysis Sensitivity analysis is a method used to understand the impact of uncertainty or variation in the input parameters or assumptions of a model on the output or results. It helps to quantify the degree to which changes in the input parameters affect the model's predictions, and to identify which input parameters have the most significant impact on the model's output. Sensitivity analysis is particu.. 2023. 3. 31. Simple example Deep learning 은 기본적으로 다음과 같은 과정을 거친다. set data -> define a model -> compile -> fit -> evaluation -> predition 모델을 정의하는 부분이 핵심이고, 성능을 결정한다. Binary classification : 8 feature를 사용해서 모델과 맞는지 아닌지 binary 결과 예측. from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense from sklearn.model_selection import train_test_split # set data X_train, X_test, y_train, y_test = train.. 2021. 5. 7. Reference Mukund Sundararajan - https://sites.google.com/site/sundararajanmukund/ - https://dblp.uni-trier.de/pid/68/3061.html - https://github.com/ankurtaly/Integrated-Gradients - https://towardsdatascience.com/understanding-deep-learning-models-with-integrated-gradients-24ddce643dbf 2021. 4. 26. 이전 1 다음
