An excess of perfection

An Appraise of KNN to the Perfection

K-Nearest Neighbor (KNN) is highly efficient classification algorithm due to its key features like: very easy to use, requires low training time, robust to noisy training data, easy to implement. However, it also has some shortcomings like high computational complexity, large memory requirement for large training datasets, curse of dimensionality and equal weights given to all attributes. Many ...

Perfection thickness of graphs

We determine the order of growth of the worst-case number of perfect subgraphs needed to cover an n-vertex graph.

Regenerating Perfection.

Testing perfection is hard

A graph property P is strongly testable if for every fixed > 0 there is a one-sided -tester for P whose query complexity is bounded by a function of . In classifying the strongly testable graph properties, the first author and Shapira showed that any hereditary graph property (such as P the family of perfect graphs) is strongly testable. A property is easily testable if it is strongly testable ...

Profiling, Performance, and Perfection

A profile is “a set of data often in graphic form portraying the significant features of something”. [Web88] Profiles can help us to quickly understand a person or entity better. In the development of computer-based applications, profiles are invaluable. They help us to understand the application – how it works, how well it works, whether it in fact works as we think it does, and whether it is ...