pythondeep-learningkerasanomaly-detectionone-class-learningone-classone-class-classificationintra-class-splitting UpdatedJun 25, 2019 Python A set of tools to rank molecular pairs by their similarity to components of co-crystal reported in the CSD. ...
77 - Day 4 Building CNN Architectures with Keras and TensorFlow 17:47 78 - Day 5 Building CNN Architectures with PyTorch 22:27 79 - Day 6 Regularization and Data Augmentation for CNNs 18:41 80 - Day 7 CNN Project Image Classification on Fashion MNIST or CIFAR10 27:35 81 - Introd...
For our proposed OC-LSTM, TensorFlow [34] and Keras were used for the experiment. All the experimental results are the average performances obtained with the 10-fold cross-validation method. 5.1. One-Class Classification on NSL-KDD NSL-KDD contained four different anomaly categories from which ...
Data preprocessing was carried out using Pandas (1.5.2) and NumPy (1.26.0), while machine learning and deep learning tasks were handled using Scikit-learn (1.1.3) and Keras with TensorFlow (2.10.0), respectively. 4.2. Performance Evaluation Metrics Different performance evaluation metrics were ...
9. Visualization by Keras I also tried visualization with Grad-CAM. It is also important to visualize where abnormality is. 9-1. Grad-CAM Grad-CAM is often used for CNN classification problems. When used in a classification problem, it shows the part that became the basis of that classifica...
For our proposed OC-LSTM, TensorFlow [34] and Keras were used for the experiment. All the experimental results are the average performances obtained with the 10-fold cross-validation method. 5.1. One-Class Classification on NSL-KDD NSL-KDD contained four different anomaly categories from which ...