Abstract The “Big Data” era has arisen, driven by the increasing availability of data from
multiple sources such as social media, online transactions, network sensors or mobile …

Human experts constitute pattern classes of natural objects based on their observed
appearance. Automatic systems for pattern recognition may be designed on a structural …

The patterns in collections of real world objects are often not based on a limited set of
isolated properties such as features. Instead, the totality of their appearance constitutes the …

In multiple instance learning, objects are sets (bags) of feature vectors (instances) rather
than individual feature vectors. In this paper, we address the problem of how these bags can …

In this chapter, we consider instance selection as an important focusing task in the data
reduction phase of knowledge discovery and data mining. First of all, we define a broader …

In many pattern recognition applications, object structure is essential for the discrimination
purpose. In such cases, researchers often use recognition schemes based on template …

摘要作为一种简单而成熟的分类方法, K 最近邻(K nearest neighbor, KNN) 算法在数据挖掘,
模式识别等领域获得了广泛的应用, 但仍存在计算量大, 高空间消耗, 运行时间长等问题 …

How to select the prototypes for classification in the dissimilarity space remains an open and
interesting problem. Especially, achieving scalability of the methods is desirable due to …

Dissimilarity representation plays a very important role in pattern recognition due to its ability
to capture structural and relational information between samples. Dissimilarity space …

Methods for tackling classification problems usually maximize prediction accuracy. However
some applications require maximum predictive value instead. That is, the designer hopes to …