计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
17期
112-115
,共4页
自组织映射%神经网络%高维数据可视化%聚类分析
自組織映射%神經網絡%高維數據可視化%聚類分析
자조직영사%신경망락%고유수거가시화%취류분석
self-organizing map%neural networks%data visualization%clustering analysis
通过对高维数据可视化方法的系统研究，提出了一种新的基于自组织映射（Self-Organizing Map，SOM）的算法。为了表现该方法的特点，将其称为三维自组织映射（Three-Dimensional SOM，TDSOM）。它在对高维数据记录集进行SOM分析后将其投影到三维坐标系中的特定的点集上，最终形成三维模型。该模型弥补了传统模型难以清晰准确地展现高维数据的缺陷，并且新模型着重于在一个比二维平面更为广阔的三维立体空间中展现海量数据。使用者通常可以根据当前领域的专业知识在分析模型的基础上得出有意义的模式。新方法可以广泛使用在数据挖掘和模式识别等领域。
通過對高維數據可視化方法的繫統研究，提齣瞭一種新的基于自組織映射（Self-Organizing Map，SOM）的算法。為瞭錶現該方法的特點，將其稱為三維自組織映射（Three-Dimensional SOM，TDSOM）。它在對高維數據記錄集進行SOM分析後將其投影到三維坐標繫中的特定的點集上，最終形成三維模型。該模型瀰補瞭傳統模型難以清晰準確地展現高維數據的缺陷，併且新模型著重于在一箇比二維平麵更為廣闊的三維立體空間中展現海量數據。使用者通常可以根據噹前領域的專業知識在分析模型的基礎上得齣有意義的模式。新方法可以廣汎使用在數據挖掘和模式識彆等領域。
통과대고유수거가시화방법적계통연구，제출료일충신적기우자조직영사（Self-Organizing Map，SOM）적산법。위료표현해방법적특점，장기칭위삼유자조직영사（Three-Dimensional SOM，TDSOM）。타재대고유수거기록집진행SOM분석후장기투영도삼유좌표계중적특정적점집상，최종형성삼유모형。해모형미보료전통모형난이청석준학지전현고유수거적결함，병차신모형착중우재일개비이유평면경위엄활적삼유입체공간중전현해량수거。사용자통상가이근거당전영역적전업지식재분석모형적기출상득출유의의적모식。신방법가이엄범사용재수거알굴화모식식별등영역。
A new high-dimensional data visualization algorithm based on the Self-Organizing Map(SOM)is demonstrated. The algorithm is named TDSOM(Three-Dimensional Self-Organizing Map) to describe its special characteristics. After being trained with SOM network, high-dimensional data is projected into particular point sets in the three-dimensional coordinate sys-tem. A three-dimensional model is created by the algorithm. Through the experiment, TDSOM is proved to be much more accu-rate and more analytical than the traditional methods in displaying the high-dimensional data. The main innovation of the new TDSOM algorithm is the presentation of the large data in three-dimensional coordinate system which is much vaster than the two-dimensional one. What’s more, users are able to discover some interesting patterns according to their own areas through the model. The method can be widely applied in areas such as data mining, pattern recognition and so on.
