Classification of the cardiotocogram data for anticipation of fetal risks using machine learning techniques

- Cardiotocography (CTG) is used as a technique of measuring fetal well-being.
- The classification performances of different classification methods are examined.
- The research showed us there is no big difference in accuracies of the classifiers.
- The accuracy achieved by k-NN is 98.4% (minimum) and by RF is 99.18% (maximum).