In the literature, most of the researchers used the confusion matrix values as the performance measure. The four values in the confusion matrix (true positives (TP), false positives (FP), true negatives (TN), and false negatives (FN)) can be used to calculate many other metrics, including...
2870 Accesses 6 Citations 2 Altmetric Metrics details Abstract Modern machine learning (ML) and deep learning (DL) techniques using high-dimensional data representations have helped accelerate the materials discovery process by efficiently detecting hidden patterns in existing datasets and linking input ...
loop nest cost = --metrics #intrinsic cache-usage Task scheduler Use same timeslice for all subgraph in the firstiteration, and get the gradient of improvement dy/dt, the biggest value means this subgraph is worth to tune and will give it more timeslice in the next iteration. Key contribut...
5814 Accesses Metrics details Abstract We evaluated the diagnostic performance and generalizability of traditional machine learning and deep learning models for distinguishing glioblastoma from single brain metastasis using radiomics. The training and external validation cohorts comprised 166 (109 glioblastomas ...
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) # Fit the model model.fit(X, Y, validation_split=0.33, epochs=150, batch_size=10) Note: Your results may vary given the stochastic nature of the algorithm or evaluation procedure, or differences in numerical...
It is now well established that more than one performance metrics are necessary for evaluating a multi-objective evolutionary algorithm (MOEA). Although there exist a number of performance metrics in the MOEA literature, most of them are applied to the final non-dominated set obtained by an MOEA...
Generalized additive models (GAM) are shown to be effective in modelling DL performance metrics based on the number of training images per class, tuning scheme and dataset. Key-words: Camera Traps, Deep Learning, Ecological Informatics, Generalised Additive Models, Learning Curves, Predictive ...
We recommend that you monitor the output of iostat(1)in conjunction with the output of whatever disk IO load generator tool is being used. This allows us to validate the various metrics provided by the load generator tool as well as ensure that we’re seeing disk IO and not cache IO. Io...
3740 Accesses 117 Citations 37 Altmetric Metrics details A preprint version of the article is available at arXiv.Abstract Recent research has demonstrated that feature attribution methods for deep networks can themselves be incorporated into training; these attribution priors optimize for a model whose ...
The appropriate metrics have been selected and implemented. These should be as representative as possible of what would be measured in the deployed environment.Choosing the model architectureSummary: When starting a new project, try to reuse a model that already works.Choose...