Sentence examples for sample imbalance problem from inspiring English sources

With this cumulative hidden layer, our model is learnt indirectly using faces with neighbouring ages and thus alleviate the sample imbalance problem.

To combat the sample imbalance problem, we propose a novel cumulative hidden layer which is supervised by a point-wise cumulative signal.

Secondly, the number of non-interaction sites is much more than interaction sites, which leads to a sample imbalance problem, and hence biased machine learning model with preference to non-interaction sites.

In addition, the SMOTE (Synthetic Minority Over-sampling Technique) algorithm is adopted to resample fault samples in order to solve the serious imbalance problem of samples.

The first comparison experiment demonstrates the SVM with mix-ratio sampling method relieves the imbalance problem for multiclass more effectively and efficiently than the SVM with simple over-sampling method.

We use two approaches to deal with the imbalance problem: sampling methods and cost-sensitive learning.

There are two main ways to overcome an imbalance problem: over-sampling the minority class and under-sampling the majority class.

Second, while the numbers of negative and positive samples were similar in the previous study, the number of hypertensive samples in our study was less than that of normal subject samples, resulting in a class imbalance problem.

In reality, the number of negative samples is far greater than positive samples, which forms the severe class imbalance problem.

However, in our case, sample imbalance did not seem to be a problem: we ran the classifier with different ratios of non-W W conon-W Wfrom 1:1 to 100:1) in the training set and found no significontigsfromences in performance.

In this paper, a novel inverse random under sampling (IRUS) method is proposed for the class imbalance problem.