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The goal of the presented work consists in the construction of the new three-levels scheme of authomatical classification. This scheme is based on the newly introduced notion of volatility of separate clusters as well as of whole classification. The property is exactly defined and efficiently calculated. It describes the stability, exactness, validity of subsets of the given initial set in essence, their possibility (or impossibility) to be selected as clusters. The suggested algorithm finds the clusters with arbitrary levels of volatility, including the conventional case of zero volatility. The clusters in USA, Russia and Sweden stock market (for crisis period of 2008-2010) and deputies clusters based on voting results in the 3rd State Duma between September 2001 and January 2002 (the period including the creation of the party "United Russia" 01.12.2001) were constructed by the suggested algorithm. Analyzing clusters constructed basing on the voting results for every of the considered months, it has turned out that the clustering volatility was equal to zero in September and October, drastically increased in November and slightly decreased in December and January. But several indices (i.e. concordance of parties' positions) did not show sensible jumps near this political "bifurcation point". The other considered various model examples demonstrated the results well-coordinated with geometrical intuition.

In this paper, a new hybridization of supervised principal component analysis (SPCA) and stochastic gradient descent techniques is proposed, and called as SGD-SPCA, for real large datasets that have a small number of samples in high dimensional space. SGD-SPCA is proposed to become an important tool that can be used to diagnose and treat cancer accurately. When we have large datasets that require many parameters, SGD-SPCA is an excellent method, and it can easily update the parameters when a new observation shows up. Two cancer datasets are used, the first is for Leukemia and the second is for small round blue cell tumors. Also, simulation datasets are used to compare principal component analysis (PCA), SPCA, and SGD-SPCA. The results show that SGD-SPCA is more efficient than other existing methods.

Broadband communication technologies offer households many opportunities, including greater access to education, health and government services, entertainment and social connectivity. Australia appears, however, to be lagging behind other nations in adopting broadband. This paper reports on a study of the relative importance of factors affecting broadband uptake and usage by Australian households. A large data set with 23,093 records was analysed using an innovative statistical technique known as classification tree analysis. Important adoption factors, in approximate order of importance, were: Frequency of Internet usage (indicating needs and benefits of use); Location, a factor likely to indicate, in part, the availability of services; Technophilia, a tendency to acquire technologies in general in the household; and Subscription to Pay TV. User needs and benefits, rather than cost, were found to be primary drivers.

Proceedings of: 6th International Conference The Non-Linear Speech Processing (NOLISP 2013). Mons, Belgium, June 19-21, 2013. ; In this paper, we propose a new front-end for Acoustic Event Classification tasks (AEC). First, we study the spectral contents of different acoustic events by applying Non-Negative Matrix Factorization (NMF) on their spectral magnitude and compare them with the structure of speech spectra. Second, from the findings of this study, we propose a new parameterization for AEC, which is an extension of the conventional Mel Frequency Cepstrum Coefficients (MFCC) and is based on the high pass filtering of acoustic event spectra. Also, the influence of different frequency scales on the classification rate of the whole system is studied. The evaluation of the proposed features for AEC shows that relative error reductions about 12% at segment level and about 11% at target event level with respect to the conventional MFCC are achieved. ; This work has been partially supported by the Spanish Government grants TSI-020110-2009-103, IPT-120000-2010-24 and TEC2011-26807. Financial support from the Fundaci´on Carolina and Universidad Católica San Pablo, Arequipa. ; Publicado

Text contains a wealth of information about about a wide variety of sociocultural constructs. Automated prediction methods can infer these quantities (sentiment analysis is probably the most well-known application). However, there is virtually no limit to the kinds of things we can predict from text: power, trust, misogyny, are all signaled in language. These algorithms easily scale to corpus sizes infeasible for manual analysis. Prediction algorithms have become steadily more powerful, especially with the advent of neural network methods. However, applying these techniques usually requires profound programming knowledge and machine learning expertise. As a result, many social scientists do not apply them. This Element provides the working social scientist with an overview of the most common methods for text classification, an intuition of their applicability, and Python code to execute them. It covers both the ethical foundations of such work as well as the emerging potential of neural network methods.

Broadband communication technologies offer households many opportunities, including greater access to education, health and government services, entertainment and social connectivity. Australia appears, however, to be lagging behind other nations in adopting broadband. This paper reports on a study of the relative importance of factors affecting broadband uptake and usage by Australian households. A large data set with 23,093 records was analysed using an innovative statistical technique known as classification tree analysis. Important adoption factors, in approximate order of importance, were: Frequency of Internet usage (indicating needs and benefits of use); Location, a factor likely to indicate, in part, the availability of services; Technophilia, a tendency to acquire technologies in general in the household; and Subscription to Pay TV. User needs and benefits, rather than cost, were found to be primary drivers.

The article analyzes the state control of civil aviation. A comparative analysis of various regulations in the field of civil aviation is conducted. It is concluded that there is a need to improve state control in the field of civil aviation. Civil aviation creates significant risks for businesses, the environment, society, and is at the same time an organic component of social and scientific and technological development. To date, the question of signs of state control of civil aviation in Ukraine has been almost unexplored. In addition, the issues of administrative and legal regulation of general aviation are unresolved. State control in the field of civil aviation is of great importance today. This is related to the rapid development of aviation, scientific and technological progress, European integration processes in Ukraine. The analysis of the domestic legislation leads to the conclusion that in Ukraine there is no single definition of general aviation, this raises a number of misunderstandings in the interpretation of activities performed by general aviation. According to Article 1 of the Air Code of Ukraine, general aviation is aviation not used for commercial air transportation and performance of aviation works. It is worth agreeing with the considerations of V. Zueva, V. Cherevatyuk that the current code does not form an idea of the subject of regulation of general aviation, therefore does not fix the possibility of carrying out any commercial activity, including conducting aviation works within the RAM, and allows for an ambiguous interpretation in the provisions of general aviation. In addition, the Code does not contain a direct prohibition on conducting commercial activities by general aviation. It is worth noting that there is no separate section in the Air Code that would regulate general aviation. Civil aviation is divided into commercial and general aviation. Today, there are different definitions of general aviation set out in various regulations. For the sake of uniform interpretation, it is ...