We present a new aggregation method - called SVM algorithm - and use this technique to produce novel measures of democracy (186 countries, 1960-2014). The method takes its name from a machine learning technique for pattern recognition and has three notable features: it makes functional...

We provide a comprehensive overview of the literature on the measurement of democracy and present an extensive update of the Machine Learning indicator of Gründler and Krieger (2016, European Journal of Political Economy). Four improvements are particularly notable: First, we produce a...

We provide a comprehensive overview of the literature on the measurement of democracy and present an extensive update of the Machine Learning indicator of Gründler and Krieger (2016, European Journal of Political Economy). Four improvements are particularly notable: First, we produce a...

Today, most of the data in business applications is stored in relational databases. Relational database systems are so popular, because they offer solutions to many problems around data storage, such as efficiency, effectiveness, usability, security and multi-user support. To benefit from these...

Today, most of the data in business applications is stored in relational database systems or in data warehouses built on top of relational database systems. Often, for more data is available than can be processed by standard learning algorithms in reasonable time. This paper presents an...

Support Vector Machines (SVMs) have become a popular tool for learning with large amounts of high dimensional data. However, it may sometimes be preferable to learn incrementally from previousSVM results, as computing a SVM is very costly in terms of time and memory consumption or because the...