(Psycho-)Analysis of Benchmark Experiments

It is common knowledge that certain characteristics of data sets -- such as linear separability or sample size -- determine the performance of learning algorithms. In this paper we propose a formal framework for investigations on this relationship. The framework combines three, in their respective scientific discipline well-established, methods. Benchmark experiments are the method of choice in machine and statistical learning to compare algorithms with respect to a certain performance measure on particular data sets. To realize the interaction between data sets and algorithms, the data sets are characterized using statistical and information-theoretic measures; a common approach in the field of meta learning to decide which algorithms are suited to particular data sets. Finally, the performance ranking of algorithms on groups of data sets with similar characteristics is determined by means of recursively partitioning Bradley-Terry models, that are commonly used in psychology to study the preferences of human subjects. The result is a tree with splits in data set characteristics which significantly change the performances of the algorithms. The main advantage is the automatic detection of these important characteristics. The framework is introduced using a simple artificial example. Its real-word usage is demonstrated by means of an application example consisting of thirteen well-known data sets and six common learning algorithms. All resources to replicate the examples are available online

Credit-Scoring Methods (in English)

The paper reviews the best-developed and most frequently applied methods of credit scoring employed by commercial banks when evaluating loan applications. The authors concentrate on retail loans – applied research in this segment is limited, though there has been a sharp increase in the volume of loans to retail clients in recent years. Logit analysis is identified as the most frequent credit-scoring method used by banks. However, other nonparametric methods are widespread in terms of pattern recognition. The methods reviewed have potential for application in post-transition countries.banking sector, credit scoring, discrimination analysis, pattern recognition, retail loans

Managerial Segmentation of Service Offerings in Work Commuting, MTI Report WP 12-02

Methodology to efficiently segment markets for public transportation offerings has been introduced and exemplified in an application to an urban travel corridor in which high tech companies predominate. The principal objective has been to introduce and apply multivariate methodology to efficiently identify segments of work commuters and their demographic identifiers. A set of attributes in terms of which service offerings could be defined was derived from background studies and focus groups of work commuters in the county. Adaptive choice conjoint analysis was used to derive the importance weights of these attributes in available service offering to these commuters. A two-stage clustering procedure was then used to explore the grouping of individual’s subsets into homogeneous sub-groups of the sample. These subsets are commonly a basis for differentiation in service offerings that can increase total ridership in public transportation while approximating cost neutrality in service delivery. Recursive partitioning identified interactions between demographic predictors that significantly contributed to the discrimination of segments in demographics. Implementation of the results is discussed

Latihan mengajar : Keberkesanannya terhadap pelajar Diploma Kejuruteraan serta Pendidikan di KUiTTHO (Kolej Universiti Teknologi Tun Hussein Onn) menurut persepsi pelajar

Kajian yang dijaiankan adaiah bertajuk "Latihan Mengajar : Kebersanannya Terhadap Pelajar Diploma Kejuruteraan berserta Pendidikan di KUiTTHO (Kolej Universiti Teknologi Tun Hussein Onn Menurut Persepsi Pelajar. Kajian ini bertujuan untuk meiihat sejauhmana keberkesanan program latihan mengajar terhadap pelajar yang telah melaluinya. Borang soalselidik diedarkan untuk mendapatkan maklumat dan seterusnya dianalisis untuk menghasilkan skor min dan peratusan. Hasil kajian menunjukkan kebanyakan responden memberikan reaksi positif terhadap keberkesanan program latihan mengajar. Hasil dari anaiisis kajian juga, pengkaji telah menghasilkan sebuah produk iaitu senarai semak yang boleh digunakan oleh pelajar yang akan menjalani program latihan mengajar supaya pelajar jelas dengan tindakan yang harus mereka ambil sebeium, semasa dan selepas menjalani latihan mengajar. Adaiah diharapkan agar produk ini dapat membantu untuk pelajar, pihak KUiTTHO dan seterusnya institusi tempat latihan mengajar supaya program ini dapat dilaksanakan dengan Iebih sempuma dan seterusnya mencapai objektif program latihan mengajar

The impact of cultural intelligence on communication effectiveness, job satisfaction and anxiety for Chinese host country managers working for foreign multinationals

Cultural intelligence (CQ) is an important construct attracting growing attention in academic literature and describing cross-cultural competencies. To date, researchers have only partially tested the relationship between CQ and its dependent variables, such as performance. In this study, the relationship between CQ and communication effectiveness and job satisfaction is measured in a sample of 225 Chinese managers working for foreign multinational enterprises in China. The results show that CQ plays an important role in reducing anxiety and influencing both communication effectiveness and job satisfaction positively. Another outcome is the unexpected influence of anxiety on job satisfaction but not on communication effectiveness. These findings contribute to the development of theory with regard to the CQ construct

Prediction of failure in industry: An analysis of income statements

Business Failures;business economics

Identification of an Efficient Gene Expression Panel for Glioblastoma Classification.

We present here a novel genetic algorithm-based random forest (GARF) modeling technique that enables a reduction in the complexity of large gene disease signatures to highly accurate, greatly simplified gene panels. When applied to 803 glioblastoma multiforme samples, this method allowed the 840-gene Verhaak et al. gene panel (the standard in the field) to be reduced to a 48-gene classifier, while retaining 90.91% classification accuracy, and outperforming the best available alternative methods. Additionally, using this approach we produced a 32-gene panel which allows for better consistency between RNA-seq and microarray-based classifications, improving cross-platform classification retention from 69.67% to 86.07%. A webpage producing these classifications is available at http://simplegbm.semel.ucla.edu

A SUMMARY OF Classification and Regression Tree WITH APPLICATION

Classification and regression tree (CART) is a non-parametric methodology that was introduced first by Breiman and colleagues in 1984. CART is a technique which divides populations into meaningful subgroups that allows the identification of groups of interest. CART as a classification method constructs decision trees. Depending on information that is available about the dataset, a classification tree or a regression tree can be constructed. The first part of this paper describes the fundamental principles of tree construction, pruning procedure and different splitting algorithms. The second part of the paper answers the questions why or why not the CART method should be used or not. The advantages and weaknesses of the CART method are discussed and tested in detail. Finally, CART is applied to an example with real data, using the statistical software R. In this paper some graphical and plotting tools are presented