We instrument a system for recognizing handwritten mathematical expressions using the Recognition Strategy Library, a data provenance tool for pattern recognition research, in order to study the behavior of the recognition system and demonstrate the utility of the library. In this case study, the library was used to perform comparison tests to quantitatively analyze several modifications to the...

artificial immune systems (ais) can be defined as soft computing systems inspired by immune system of vertebrates. immune system is an adaptive pattern recognition system. ais have been used in pattern recognition, machine learning, optimization and clustering. feature reduction refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encoun...

The information era has witnessed an explosion in the collection of data that contain potentially useful information for a wide range of applications such as biology, sociology, pattern recognition, marketing and finance. As a result of this inflation, statisticians have developed a new set of tools that combine fundamental statistical concepts with profoundly new ideas. This set of problems an...

I'll show in an initial section (1.) that the kind of analogy between life and information (argue for by authors such as [1], [2], [3] [4], [5], [6]) is like the design argument and that if the design argument is invalid, the argument to the effect that artificial mind may represents an expected advance in the life evolution in Universe is also unfounded and invalid. However, if we are prepared...

An introduction into the setup, definitions and use of PRTools is given. Readers are assumed to be familiar with Matlab and should have a basic understanding of field of statistical pattern recognition. The Netherlands-2

Data mining is the task of discovering interesting patterns from large amounts of data. There are many data mining tasks, such as classification, clustering, association rule mining, and sequential pattern mining. Sequential pattern mining is the process of finding the relationships between occurrences of sequential events, to find if there exists any specific order of the occurrences. It is a ...

Sequential pattern mining deals with data represented as sequences (a sequence contains sorted sets of items). Compared to the association rule problem, a study of such data provides “inter-transaction” analysis (Agrawal & Srikant, 1995). Applications for sequential pattern extraction are numerous and the problem definition has been slightly modified in different ways. Associated to elegant sol...

Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all pairwise distances between patterns must be computed in advance. This makes it computationally expensive and difficult to cope with large scale data used in several applications, such as in bioinformatics. In this paper we propo...