This paper presents the CATS Benchmark and the results of the competition organised during the IJCNN’04 conference in Budapest. Twenty-four papers and predictions have been submitted and seventeen have been selected. The goal of the competition was the prediction of 100 missing values divided into five groups of twenty consecutive values.

Stocks with similar financial ratio values across years have similar price movements. We investigate this hypothesis by clustering groups of stocks that exhibit homogeneous financial ratio values across years, and then study their price movements. We propose using Cross-Graph Quasi-Biclique (CGQB) subgraphs to cluster stocks, as they can define the three dimensional (3D) subspaces of financial ...

Organizational social capital is critical to effective organizational functioning. Yet, different aspects of social capital are likely to be present to varying degrees within any given organization. In this study, alternative blends of structural, relational and cognitive social capital are modelled using a range of key organizational variables drawn from an incomplete dataset. A novel evidence...

Reliability measures in linear models are used in geodetic science and elsewhere to quantify the potential to detect outliers and to suppress their impact on the regression estimates. Here we shall study the eeect of missing values on these reliability measures with the idea that, under a proper design, they should not change drastically when such a situation occurs.

We address the problem of learning over multiple inter-dependent temporal sequences where dependencies are modeled by a graph. We propose a model that is able to simultaneously fill in missing values and predict future ones. This approach is based on representation learning techniques, where temporal data are represented in a latent vector space. Information completion (missing values) and pred...

Missing data are a common occurrence in survey-based research studies in education, and the way missing values are handled can significantly affect the results of analyses based on such data. Despite known problems with performance of some missing data handling methods, such as mean imputation, many researchers in education continue to use those methods as a quick fix. This study reviews the cu...

The Cornell Laboratory of Ornithology’s mission is to interpret and conserve the earth’s biological diversity through research, education, and citizen science focused on birds. Over the years, the Lab has accumulated one of the largest and longest-running collections of environmental data sets in existence. The data sets are not only large, but also have many attributes, contain many missing va...

The paper presents a comparative study of the performance of Back Propagation and Instance Based Learning Algorithm for classification tasks. The study is carried out by a series of experiments will all possible combinations of parameter values for the algorithms under evaluation. The algorithm's classification accuracy is compared over a range of datasets and measurements like Cross Validation...

Knowledge monitoring is an important metacognitive process which can help students improve study habits and thereby increase academic performance. Which is more useful in predicting test performance: knowing what you know, or knowing what you do not know? Two distinct constructs of knowledge monitoring calibration, sensitivity and specificity, were used along with the more traditional Gamma to ...

Nuclear safeguards evaluation aims to verify that countries are not misusing nuclear programs for nuclear weapons purposes. Experts of the International Atomic Energy Agency (IAEA) carry out an evaluation process in which several hundreds of indicators are assessed according to the information obtained from different sources, such as State declarations, on-site inspections, IAEA non-safeguards ...