================== Euclidean Distance ================== The Euclidean distance for real valued features is the square root of the sum of squared disparity between the corresponding feature dimensions of two data points. .. math:: d({\bf x},{\bf x'})= \sqrt{\sum_{i=0}^{d}|{\bf x_i}-{\bf x'_i}|^2} where :math:`\bf x` and :math:`\bf x'` are :math:`d` dimensional feature vectors. ------- Example ------- Imagine we have files with data. We create CDenseFeatures (here 64 bit floats aka RealFeatures) as .. sgexample:: euclidean.sg:create_features We create an instance of :sgclass:`CEuclideanDistance` by passing it :sgclass:`CDenseFeatures`. .. sgexample:: euclidean.sg:create_instance Distance matrix can be extracted as follows: .. sgexample:: euclidean.sg:extract_distance We can use the same instance with new :sgclass:`CDenseFeatures` to compute distance. .. sgexample:: euclidean.sg:refresh_distance If desired, squared distance can be extracted like: .. sgexample:: euclidean.sg:extract_sq_distance ---------- References ---------- :wiki:`Euclidean_distance` .. bibliography:: ../../references.bib :filter: docname in docnames