Cube High-Dimensional Data Visualization Algorithm Research

Cube contains vast amounts of complex data, how to carry on the scientific understanding and analysis of the data and use, is an important and difficult topic in the field of data mining. For traditional visualization algorithm can't solve the problem of high-dimensional data visualization of multiple attribute, the deficiencies of the algorithm is less complex, applicability, visualization algorithm based on fast data clustering is proposed. Algorithm firstly builds a kind of multidimensional data model, trigonometric polynomial is adopted to establish the mapping relation; The cube for different levels of division, and based on clustering effect to screen the optimal clustering number; Finally based on parallel coordinates, temporal multi-dimensional analysis of high-dimensional data, improve the robustness of the algorithm. Experiments prove that the proposed algorithm is concise and easy to use, can well realize the cube understanding and analysis of high-dimensional data.