Analysis Of An Intelligence Dataset
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Analysis of an Intelligence Dataset
In this issue, psychometrics researchers were invited to make reanalyses or extensions of a previously published dataset from a recent paper by Myszkowski and Storme (2018). The dataset analyzed consisted of responses to a multiple-choice logical reasoning nonverbal test, comprising the last series of Raven’s (1941) Standard Progressive Matrices. Although the original paper already proposed several modeling strategies, this issue presents new or improved procedures to study the psychometrics properties of tests of this type.
Intelligent Data Analysis
This monograph is a detailed introductory presentation of the key classes of intelligent data analysis methods. The twelve coherently written chapters by leading experts provide complete coverage of the core issues. The first half of the book is devoted to the discussion of classical statistical issues, ranging from the basic concepts of probability, through general notions of inference, to advanced multivariate and time series methods, as well as a detailed discussion of the increasingly important Bayesian approaches and Support Vector Machines. The following chapters then concentrate on the area of machine learning and artificial intelligence and provide introductions into the topics of rule induction methods, neural networks, fuzzy logic, and stochastic search methods. The book concludes with a chapter on Visualization and a higher-level overview of the IDA processes, which illustrates the breadth of application of the presented ideas.
Data Analysis, Machine Learning and Applications
Author: Christine Preisach
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-04-13
Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medical science, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft für Klassifikation - GfKl). The conference was held at the Albert-Ludwigs-University in Freiburg, Germany, in March 2007.