Kybernetika

Small learning-set properties of the Euclidean distance, the Parzen window, the minimum empirical error and the nonlinear single layer perceptron classifiers depend on an ``intrinsic dimensionality'' of the data, however the Fisher linear discriminant function is sensitive to all dimensions. There is no unique definition of the ``intrinsic dimensionality''. The dimensionality of the subspace where the data points are situated is not a sufficient definition of the ``intrinsic dimensionality''. An exact definition depends both, on a true distribution of the pattern classes, and on the type of the classifier used.