However, under experimental conditions performed in those experiments imbalance of NADPH level caused by metyrapone alone was not sufficient to induce autophagic events or viability alterations.
We calculated the SN, SP, and GM values of model1 and illustrated the results in Figure 7. Experiment 2 The imbalanced test set was tested by model1 achieved in Experiment 1, and the SN, SP, and GM values of the test results were calculated.
The number of deformities increased throughout the experiment and an imbalanced bone and cartilage production characterized susceptible fish, predisposed for developing deformities [ 23].
Our goal was to test equal numbers of males and females from each strain; however, the final experiment was slightly imbalanced due to unequal sex ratios in the Nadia (male-biased) and SH (female-biased) strains.
Experiments on benchmark imbalanced data sets demonstrate that our approach accomplishes the best classification performance, compared with the traditional SOCP-SVM formulation and with cost-sensitive formulations for linear SVM.
We performed experiments on 12 highly imbalanced microarray datasets using linear and Gaussian kernel, achieving the highest average predictive performance with our approach compared with the most well-known feature selection strategies.
Our experiments on five highly imbalanced splice site datasets, with positive to negative ratios of 1-to-99, showed that the ensemble-based semi-supervised approaches represent a good choice, even when the amount of labeled data consists of less than 1% of all training data.
Five groups of SN, SP, and GM values corresponding to the five training sets are shown in Figure 9. Five groups of feature vectors are detailed Section 2. Experiment 4 We tested the imbalanced testing dataset with model1, model2, model3, model4, and model5 in this order.
The Random Forest implementation from Mahout2 [56] 56] was selected as baseline classifier for the experiments, applied over three different imbalanced Big Data problems from the UCI dataset repository [57], with up to 6 millions of instances.
For social network imbalanced data, some experiments are conducted using our weighted ELM based on the overall distribution, named ODW-ELM, to deal with binary classification and multi-class classification tasks.
