Discovering Regression Rules with Ant Colony Optimization

The majority of Ant Colony Optimization (ACO) algorithms for data mining have dealt with classification or clustering problems. Regression remains an unexplored research area to the best of our knowledge. This paper proposes a new ACO algorithm that generates regression rules for data mining applications. The new algorithm combines components from an existing deterministic (greedy) separate and conquer algorithm—employing the same quality metrics and continuous attribute processing techniques—allowing a comparison of the two. The new algorithm has been shown to decrease the relative root mean square error when compared to the greedy algorithm. Additionally a different approach to handling continuous attributes was investigated showing further improvements were possible

Entrepreneurial entry: which institutions matter?

In this paper we explore the relationship between the individual decision to become an entrepreneur and the institutional context. We pinpoint the critical roles of property rights and the size of the state sector for entrepreneurial activity and test the relationships empirically by combining country-level institutional indicators for 44 countries with working age population survey data taken from the Global Enterprise Monitor. A methodological contribution is the use of factor analysis to reduce the statistical problems with the array of highly collinear institutional indicators. We find that the key institutional features that enhance entrepreneurial activity are indeed the rule of law and limits to the state sector. However, these results are sensitive to the level of development

Data mining as a tool for environmental scientists

Over recent years a huge library of data mining algorithms has been developed to tackle a variety of problems in fields such as medical imaging and network traffic analysis. Many of these techniques are far more flexible than more classical modelling approaches and could be usefully applied to data-rich environmental problems. Certain techniques such as Artificial Neural Networks, Clustering, Case-Based Reasoning and more recently Bayesian Decision Networks have found application in environmental modelling while other methods, for example classification and association rule extraction, have not yet been taken up on any wide scale. We propose that these and other data mining techniques could be usefully applied to difficult problems in the field. This paper introduces several data mining concepts and briefly discusses their application to environmental modelling, where data may be sparse, incomplete, or heterogenous

On the role of pre and post-processing in environmental data mining

The quality of discovered knowledge is highly depending on data quality. Unfortunately real data use to contain noise, uncertainty, errors, redundancies or even irrelevant information. The more complex is the reality to be analyzed, the higher the risk of getting low quality data. Knowledge Discovery from Databases (KDD) offers a global framework to prepare data in the right form to perform correct analyses. On the other hand, the quality of decisions taken upon KDD results, depend not only on the quality of the results themselves, but on the capacity of the system to communicate those results in an understandable form. Environmental systems are particularly complex and environmental users particularly require clarity in their results. In this paper some details about how this can be achieved are provided. The role of the pre and post processing in the whole process of Knowledge Discovery in environmental systems is discussed

The category proliferation problem in ART neural networks

This article describes the design of a new model IKMART, for classification of documents and their incorporation into categories based on the KMART architecture. The architecture consists of two networks that mutually cooperate through the interconnection of weights and the output matrix of the coded documents. The architecture retains required network features such as incremental learning without the need of descriptive and input/output fuzzy data, learning acceleration and classification of documents and a minimal number of user-defined parameters. The conducted experiments with real documents showed a more precise categorization of documents and higher classification performance in comparison to the classic KMART algorithm.Web of Science145634

Entrepreneurial Entry: Which Institutions Matter?

In this paper we explore the relationship between the individual decision to become an entrepreneur and the institutional context. We pinpoint the critical roles of property rights and the size of the state sector for entrepreneurial activity and test the relationships empirically by combining country-level institutional indicators for 44 countries with working age population survey data taken from the Global Enterprise Monitor. A methodological contribution is the use of factor analysis to reduce the statistical problems with the array of highly collinear institutional indicators. We find that the key institutional features that enhance entrepreneurial activity are indeed the rule of law and limits to the state sector. However, these results are sensitive to the level of development.entrepreneurship, property rights, access to finance

Entrepreneurship in transition economies: the role of institutions and generational change

The transition economies have lower rates of entrepreneurship than are observed in most developed and developing market economies. The difference is even more marked in the countries of the former Soviet Union than those of Central and Eastern Europe. We link these differences partly with the legacy of communist planning, which needs to be replaced with formal market-supporting institutions. But many of these developments have now taken place, yet entrepreneurial activity still remains low in many places. To analyse this longer term issue, we highlight the necessarily slow pace of development of new informal institutions and the corresponding social attitudes, notably rebuilding the generalised trust. We argue that changes are even slower in the former Soviet Union than Central and Eastern Europe because communist rule was much longer, leading to a lack of institutional memory. We posit that changes in informal institutions may be therefore delayed until after full generational change

Drawing Boundaries for Air Quality Control Under the Clean Air Act: The Importance of NOT Being Nonattainment

Much has changed with regard to air pollution control since 1970 whenCongress revised the Clean Air Act to assume a form that, in very broad terms,it retains today.  From a legal point of view, while states1 still retained at thattime wide-ranging discretion to design the regulatory controls necessary toattain the air quality goals of the Act, that discretion was significantly limitedwhen Congress revisited the Act in 1977.  State discretion diminished to aneven greater extent, particularly with regard to the air pollutants ozone, carbonmonoxide, and particulate matter, when President George H.W. Bush signedthe Clean Air Act Amendments of 1990.</jats:p

Size matters: entrepreneurial entry and government

We explore the country-specific institutional characteristics likely to influence an individual's decision to become an entrepreneur. We focus on the size of the government, on freedom from corruption, and on 'market freedom' defined as a cluster of variables related to protection of property rights and regulation. We test these relationships by combining country-level institutional indicators for 47 countries with working age population survey data taken from the Global Entrepreneurship Monitor. Our results indicate that entrepreneurial entry is inversely related to the size of the government, and more weakly to the extent of corruption. A cluster of institutional indicators representing 'market freedom' is only significant in some specifications. Freedom from corruption is significantly related to entrepreneurial entry, especially when the richest countries are removed from the sample but unlike the size of government, the results on corruption are not confirmed by country-level fixed effects models