Machine Learning Democracy Index
Machine Learning Democracy Index
We present democracy indices for 0 countries and the period from to . To create these indices, we use a Machine Learning tool for pattern recognition, known as Support Vector Machines (SVM). The main advantage of our approach is that we can avoid simplistic assumptions about the functional relationship between the regime characteristics and the level of democracy. Our research suggests that this methodological innovation greatly improves the measurement of democracy.
Key features:
We present democracy indices for 0 countries and the period from to . To create these indices, we use a Machine Learning tool for pattern recognition, known as Support Vector Machines (SVM). The main advantage of our approach is that we can avoid simplistic assumptions about the functional relationship between the regime characteristics and the level of democracy. Our research suggests that this methodological innovation greatly improves the measurement of democracy.
Key features:
- Countinuous and dichotomous measures of democracy.
- Data aggregation via Machine Learning method.
- 0 countries, -
- Realistic concept of democracy.
- Confidence intervals that indicate measurement uncertainty.
