(ICW-SVM) to treat imbalance credit card transactions data.Bentley et al. (2000) proposed a neural fraud detection system with fraud density map to improve the detection efficiency in context of biased train data due to skewed distribution of data.Pozzolo et al. (2013) proposed to use a ...
2022, IEEE Transactions on Emerging Topics in Computing PERCIVAL: Open-Source Posit RISC-V Core With Quire Capability 2022, IEEE Transactions on Emerging Topics in Computing PositNN: Training deep neural networks with mixed low-precision posit 2021, ICASSP, IEEE International Conference on Acoustics,...
The dataset has not be split into training and test sets, which we create ourselves, detailed later. Amazon-Google The Amazon-Google dataset consists of 1,363 tuples from Amazon and 3,226 tuples from Google, each a record of some product in their catalog or inventory. Between the two ...
This result indicates that using 80,000 sequences is enough to train classification models with good generalization capacity. In order to permit a more detailed examination of results reached by RF for the dataset containing 80,000 sequences, its confusion matrix is shown in Figure 8. Figure 8...
aGiven the large number of transactions from countries with different levels of financial development in our dataset, we are able to provide a direct test of several theoretical propositions on the effects private benefits of control have on the development of financial markets. 是特定的来自有在...
For each dataset, past benchmark tests have used models trained and evaluated on tuple pairs with a match to non-match ratio of1:100. Because the number of non-matches between two tables far outweighs the number of matches, we use negative sampling to generate pairs of non-matching tuples...
We performed the analyses to all-year dataset. Previous literature suggest performing the analyses by season to account for the substantial season-to-season variability in temperature and solar radiation (Ogulei et al., 2007). We compared all-year results with the results obtained when performing ...
For each dataset, past benchmark tests have used models trained and evaluated on tuple pairs with a match to non-match ratio of1:100. Because the number of non-matches between two tables far outweighs the number of matches, we use negative sampling to generate pairs of non-matching tuples...