基于密度调整的改进自适应谱聚类算法-控制与决策.PDFVIP

绗?9 鍗 绗? 鏈 鎺 鍒 涓 鍐 绛 2014 骞 9 鏈 Vol. 29 No. 9 Control and Decision Sep. 2014 鏂囩珷缂栧彿: 1001-0920 (2014) 09-1683-05 DOI: 10.13195/j.kzyjc.2013.0660 鍩轰簬瀵嗗害璋冩暣鐨勬敼杩涜嚜閫傚簲璋辫仛绫荤畻娉 鐜嬮泤鐞? 闄 鏂? 鐜嬫檽涓? 妗傚崼鍗 (涓崡澶у淇℃伅绉戝涓庡伐绋嬪闄紝闀挎矙410083) 鎽 瑕? 閽堝璋辫仛绫诲瓨鍦ㄦ瀯閫犵浉浼煎害鐭╅樀鏃跺灏哄害鍙傛暟鏁忔劅浠ュ強澶勭悊澶氶噸灏哄害鏁版嵁闆嗘晥鏋滀笉鐞嗘兂鐨勭己闄? 鎻愬嚭涓€绉 鍩轰簬瀵嗗害璋冩暣鐨勬敼杩涜嚜閫傚簲璋辫仛绫荤畻娉? 璇ョ畻娉曞皢鏍锋湰鐐规墍澶勯鍩熺殑瀵嗗害寮曞叆璋辫仛绫? 鍒╃敤瀵嗗害宸潵璋冩暣鏍锋湰鐐逛箣 闂寸殑鐩镐技搴? 浣垮叾鏇寸鍚堝疄闄呯皣绫讳腑鏍锋湰鐐归棿鐨勫唴鍦ㄥ叧绯? 鍦ㄤ竴瀹氱▼搴︿笂瑙ｅ喅浜嗗灏哄害鑱氱被闂; 鍚屾椂, 閫氳繃鏍锋湰鐐 鐨勮繎閭昏窛绂昏嚜閫傚簲寰楀埌灏哄害鍙傛暟, 浣跨畻娉曞灏哄害鍙傛暟鐩稿涓嶆晱鎰? 浠跨湡瀹為獙楠岃瘉浜嗘墍鎻愬嚭绠楁硶鐨勬湁鏁堟€у拰浼樿秺鎬? 鍏抽敭璇岤 璋辫仛绫伙紱瀵嗗害璋冩暣锛涜嚜閫傚簲锛涘昂搴﹀弬鏁帮紱澶氶噸灏哄害鏁版嵁闆 涓浘鍒嗙被鍙耳 TP181 鏂囩尞鏍囧織鐮? A Improved adaptive spectral clustering algorithm based on density adjustment WANG Ya-lin, CHEN Bin, WANG Xiao-li, GUI Wei-hua (School of Information Science and Engineering锛孋entral South University锛孋hangsha 410083锛孋hina. Correspondent: WANG Ya-lin 锛孍-mail 锛歽lwang@csu.edu.cn) Abstract: As spectral clustering is sensitive to the scaling parameter while calculating the af铿乶ity matrix and the result of clustering multi-scale dataset is not ideal, an improved adaptive spectral clustering algorithm based on density adjustment is proposed. The algorithm introduces local density of data into spectral clustering, using the density difference to adjust the similarity between sample points, which makes it more consistent with the data points鈥 internal relations of the clusters鈥 actual structure. So that it solves the multi-scale clustering problem to some extent. At the same time, the algorithm is relatively insensitive to the scaling parameter by using the distances between data points and t