Traditional sequential data analysis largely depends on the magnitude of the data with the geometric features of individual data points sometimes being regarded as noise to such analysis. To explore whether these geometric features alone carry some useful information for a better understanding of hidden facts contained in the sequential data, a new method called local position classification (L...

The main purpose of this paper is to describe a process for partitioning an N-dimensional population into k sets on the basis of a sample. The process, which is called 'k-means,' appears to give partitions which are reasonably efficient in the sense of within-class variance. That is, if p is the probability mass function for the population, S = {S1, S2, * *, Sk} is a partition of EN, and ui, i ...

The automated detection of diseases using Machine Learning Techniques has become a key research area lately. Although the computational complexity involved in analyzing a huge data set can be extremely high, nonetheless the merits of getting a desired result surely counts for the complexity involved in the task. In this paper we adopt the K-Means Clustering Algorithm with a single mean vector o...

We introduce an adaptive framework for multivariate sensor stream data reduction. The proposed method takes as input a sliding window of multivariate stream data, classifies the data in each window, and chooses reduction strategies that are most appropriate for the window. In the classification step, it discretizes the stream data into a string of symbols that characterize the signal changes an...

Modern analysis of HEP data needs advanced statistical tools to separate signal from background. A C++ package has been implemented to provide such tools for the HEP community. The package includes linear and quadratic discriminant analysis, decision trees, bump hunting (PRIM), boosting (AdaBoost and arc-x4), bagging and random forest algorithms, a multi-class learner, and interfaces to the sta...

Music genre classification systems are normally build as a feature extraction module followed by a classifier. The features are often short-time features with time frames of 10-30ms, although several characteristics of music require larger time scales. Thus, larger time frames are needed to take informative decisions about musical genre. For the MIREX music genre contest several authors derive ...

One-class classification problems have attracted a great deal of attention from various disciplines. In the present study, we attempt to extend the scope of application of the one-class classification technique to statistical process control (SPC) problems. We propose new multivariate control charts that apply the effectiveness of one-class classification to improvement of Phase I and Phase II ...

8 With the increasing development of remote sensing platforms and the evolution of sampling facilities in mining and oil industry, spatial datasets are becoming increasingly large, inform a growing number of variables and cover wider and wider areas. Therefore, it is often necessary to split the domain of study to account for radically different behaviors of the natural phenomenon over the doma...