BACKGROUND In a medical data set, data are commonly composed of a minority (positive or abnormal) group and a majority (negative or normal) group and the cost of misclassifying a minority sample as a majority sample is highly expensive. This is the so-called imbalanced classification problem. The traditional classification functions can be seriously affected by the skewed class distribution in ...

A new approach for cost-sensitive classification is proposed. We extend the framework of cost-sensitive learning to mitigate risks of huge costs occurring with low probabilities, and propose an algorithm that achieves this goal. Instead of minimizing the expected cost commonly used in cost-sensitive learning, our algorithm minimizes expected shortfall, a.k.a. conditional value-at-risk, known as...

Inventory management studies how a single firm can minimize the average cost per time unit of its inventory. In this paper we extend this analysis to situations where a collective of firms minimizes its joint inventory cost by means of cooperation. Depending on the information revealed by the individual firms, we analyze related cooperative TU games and focus on proportional division mechanisms...

1 Abstract Two types of errors can be associated with classifying data into two categories A and B: misclassifying an item in A as one of B and, conversely, misclassifying an item in B as one of A. Tight control over these two errors is needed in many practical situations. For example, an error of one type may have far more serious consequences than one of the other type. Most previous work on ...

proper forest management needs quantitative and precise estimates of forest stands characteristics. remotely sensed imageries, due to accurate and broad spatial information, has become a cost-effective tool in forest management. classification of forest attributes and generation of thematic maps are among the common applications of remote sensing. the objective of this study was to optimize the...

Software development projects inevitably accumulate defects throughout the development process. Due to the high cost that defects can incur, careful consideration is crucial when predicting which sections of code are likely to contain defects. Classification algorithms used in machine learning can be used to create classifiers which can be used sensitive classification methods attempt to make p...

We study a classification problem where each feature can be acquired for a cost and the goal is to optimize the trade-off between classification precision and the total feature cost. We frame the problem as a sequential decision-making problem, where we classify one sample in each episode. At each step, an agent can use values of acquired features to decide whether to purchase another one or wh...

This paper provides a comparative study on the different techniques of classifying human leg motions that are performed using two low-cost uniaxial piezoelectric gyroscopes worn on the leg. A number of feature sets, extracted from the raw inertial sensor data in different ways, are used in the classification process. The classification techniques implemented and compared in this study are: Baye...