This open access book as one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, automated machine learning (AutoML) is concerned with automating the machine learning processes. Metalearning and AutoML can help AI learn to control the application of different learning methods and acquire new solutions faster without unnecessary interventions from the user. This book offers a comprehensive and thorough introduction to almost all aspects of metalearning and AutoML, covering the basic concepts and architecture, evaluation, datasets, hyperparameter optimization, ensembles and workflows, and also how this knowledge can be used to select, combine, compose, adapt and configure both algorithms and models to yield faster and better solutions to data mining and data science problems. It can thus help developers to develop systems that can improve themselves through experience. This book is a substantial update of the first edition published in 2009. It includes 18 chapters, more than twice as much as the previous version. This enabled the authors to cover the most relevant topics in more depth and incorporate the overview of recent research in the respective area. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining, data science and artificial intelligence.
A major feat of research and synthesis, this book presents the first comprehensive history of the Dutch economy in the nineteenth century--an important but poorly understood piece of European economic history. Based on a detailed reconstruction of extensive economic data, the authors account for demise of the Dutch economy's golden age. After showing how institutional factors combined to make the Dutch economy a victim of its own success, the book traces its subsequent emergence as a modern industrial economy. Between 1780 and 1914, the Netherlands went through a double transition. Its economy--which, in the words of Adam Smith, was approaching a "stationary state" in the eighteenth century--entered a process of modern economic growth during the middle decades of the nineteenth. At the same time, the country's sociopolitical structure was undergoing radical transformation as the decentralized polity of the republic gave way to a unitary state. As the authors show, the dramatic transformation of the Dutch political structure was intertwined with equally radical changes in the institutional structure of the economy. The outcome of this dual transition was a rapidly industrializing economy on one side and, on the other, the neocorporatist sociopolitical structure that would characterize the Netherlands in the twentieth century. Analyzing both processes with a focus on institutional change, this book argues that the economic and political development of the Netherlands can be understood only in tandem.
Nicolaas van Wijk (1880-1941) was the founder of Slavic studies in the Netherlands and one of the greatest Slavists in general. This book describes for the first time how a scholar of the Dutch language, whose etymological dictionary of the Dutch language is still considered the best of its kind, was appointed in 1913 to the newly created Chair in Slavic languages at Leiden University and built up a tremendous reputation for himself in Eastern Europe. Van Wijk’s relations with his famous teacher, the linguist C.C. Uhlenbeck, are followed attentively, as is his postgraduate apprenticeship in Leipzig (1902-1903), where he followed August Leskien’s lectures in Slavic studies. Attention is also paid to the various aspects of Van Wijk’s enormous oeuvre covering the whole field of Slavic studies and of phonology, of which he was one of the pioneers. Van Wijk did not, however, follow the lines approved for the social conduct of a Leiden professor and was at one time suspected by the police of communist activities. His commitment to materially helping all he could from an Eastern Europe torn apart by the First World War and its aftermath was exceptional. His fascination with all things Russian is a background theme that played throughout his life and even at his death: son of a Dutch Reformed minister, the bachelor Van Wijk was buried in a grave surmounted by a Russian Orthodox cross beside his Russian foster son, who died young. This book is of interest to Slavists, linguists and cultural historians.
This open access book as one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, automated machine learning (AutoML) is concerned with automating the machine learning processes. Metalearning and AutoML can help AI learn to control the application of different learning methods and acquire new solutions faster without unnecessary interventions from the user. This book offers a comprehensive and thorough introduction to almost all aspects of metalearning and AutoML, covering the basic concepts and architecture, evaluation, datasets, hyperparameter optimization, ensembles and workflows, and also how this knowledge can be used to select, combine, compose, adapt and configure both algorithms and models to yield faster and better solutions to data mining and data science problems. It can thus help developers to develop systems that can improve themselves through experience. This book is a substantial update of the first edition published in 2009. It includes 18 chapters, more than twice as much as the previous version. This enabled the authors to cover the most relevant topics in more depth and incorporate the overview of recent research in the respective area. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining, data science and artificial intelligence.
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