To highlight the generalizability of the framework, GaNDLF was applied on both radiology and histology data for a variety of DL workloads/tasks (i.e., segmentation, regression, and classification) on multiple o
entropy is exactly the same as the negative log likelihood (these were two concepts that were originally developed independently in the field of computer science and statistics, and they are motivated differently, but it turns out that they compute excactly the same in our classification context.)...
The cross-dataset evaluation supports OnClass as a robust method for automated cell type classification in datasets with large numbers of unseen cell types. Fig. 4: Training with different datasets and proportions of unseen cell types highlights OnClass versatility and accuracy. a–d Heatmaps ...
This paper improves a Single-Player Monte-Carlo Tree Search (SP-MCTS) SameGame pro-gram by tuning its parameters with the Cross-Entropy Method (CEM). SP-MCTS can be used in two ways: (1) constructing one tree for the whole game and (2) constructing a tree for each move. Both approac...
The CrossEntropyWithSoftmax function specifies that cross-entropy error should be used when calculating how close calculated output values are to actual output values in the training data. Cross-entropy error is the standard metric but squared error is an alternative. ...
CEM - Cross Entropy Method OriginalCEM: Rubinstein, R. (1999). The cross-entropy method for combinatorial and continuous optimization. Methodology and computing in applied probability, 1(2), 127-190. CSO - Cat Swarm Optimization OriginalCSO: Chu, S. C., Tsai, P. W., & Pan, J. S. (...
This is usually true in classification problems, but for other problems (e.g., regression problems) yy can sometimes take values intermediate between 00 and 11. Show that the cross-entropy is still minimized when σ(z)=yσ(z)=y for all training inputs. When this is the case the cross...
Section 3 is the introduction and derivation of the method. The conclusions of experiments and prospects for future work are presented in Sections 4 Experiments, 5 Conclusion, respectively. 2. Related work The detection of fake news has many related tasks, such as rumor detection (Cao et al.,...
Moreover, we analyze the cross-entropy loss function. For the purpose of model training, we set the equilibrium coefficients as follows: [β,α1,α2,α3,α4]=[0.1,1,0.2,0.2,0.2]. This paper presents the configuration of the experimental environment, which includes the utilization of an ...
Deviation-support based fuzzy ensemble of multi-modal deep learning classifiers for breast cancer prognosis prediction Article Open access 03 December 2023 SGA-Driven feature selection and random forest classification for enhanced breast cancer diagnosis: A comparative study Article Open access 30 March...