A distance based classification is one of the popular methods for classifying instances using a point-to-point distance based on the nearest neighbour or k-NEAREST NEIGHBOUR (k-NN). The representation of distance measure can be one of the various measures available (e.g. Euclidean distance, Manhattan distance, Mahalanobis distance or other specific distance measures). In this paper, we propose ...

Data classification attempts to assign a category or a class label to an unknown data object based on an available similar data set with class labels already assigned. K nearest neighbor (KNN) is a widely used classification technique in data mining. KNN assigns the majority class label of its closest neighbours to an unknown object, when classifying an unknown object. The computational efficie...

Design and implementation of attribute evaluators has received considerable attention ever since Knuth formulated the concept of attribute grammars. In particular, the class of Ordered Attribute Grammars (OAGs) has been of particular interest because practical and efficient attribute evaluators can been implemented based on the statically determined fixed plans for such grammars. Two main categ...

A k-edge colouring (not necessarily proper) of a graph with colours in {1,2,…,k} is neighbour sum distinguishing if, for any two adjacent vertices, the sums edges incident each them are distinct. The smallest value k such that G exists denoted by χ∑e(G). When we add additional restriction must be proper, then χ∑′(G). Such colourings studied on connected at least 3 vertices. There famous conject...