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Cluster Analysis Based on Artificial Immune System and Ant Algorithm

Cluster Analysis Based on Artificial Immune System and Ant Algorithm. 台北科技大學 邱垂昱、林家豪. feature. Ant algorithm Artificial immune system Auto-clustering. Immune system. 概念： 免疫系統的主要目的是在區分身體內部的所有細胞，並將它們分為病原菌（ nonself ）和非病原菌（ self ） 人體有大量的免疫細胞稱作淋巴，主要有兩種 -T 細胞和 B 細胞

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Cluster Analysis Based on Artificial Immune System and Ant Algorithm

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  1. Cluster Analysis Based on Artificial Immune System and Ant Algorithm 台北科技大學 邱垂昱、林家豪

  2. feature • Ant algorithm • Artificial immune system • Auto-clustering

  3. Immune system • 概念： • 免疫系統的主要目的是在區分身體內部的所有細胞，並將它們分為病原菌（nonself）和非病原菌（self） • 人體有大量的免疫細胞稱作淋巴，主要有兩種-T細胞和B細胞 • 當外來的抗原侵入人體，刺激細胞的增生和變異以產生相配的抗體（Antibody），之後，這些抗體就可以破壞或中和這些抗原

  4. Immunity-based Ant ClusteringAlgorithm（IACA） • 基於螞蟻的理論，相似的物件之間會有較高的費洛蒙濃度 • 免疫系統利用問題特性啟發式（problem-specific heuristic）的方法去處理解答（solution space）間的區域搜尋（local search）並進行微調（fine-tuning）的動作 • 不同群集的物件或許存在著更高的相似度，如果將這些物件集合成群可能有機會得到更好的結果

  5. IACA 流程

  6. Immune System 流程 • 分成兩個步驟 • 1.Antigens Recognition

  7. Immune System 流程 • 分成兩個步驟 • 2.Antibodies Test

  8. Definitions and Nomenclature • T：the set composed of the used objects. • Tk：the set T named k • D(i.j)：the Euclidean distance between object i and object j. • Ocenter(T)：the center of all objects in T. • Dmean(T)：the mean distance between the objects of T and the center of all objects. • ：the average of pheromone trail left on all paths beginning from object i. • ：the average of ,for all i. • ：the immune test parameter which determines how close the objects of different cluster would be applied to immune system. • TWCV：the total within cluster variance.

  9. Simulation Result • 資料集合是用Monte Carlo的方法產生，產生243筆的資料 • 群集數量及群集的成員都是已知的 • 用誤判率（misclassified rate）和總群集內部變異量（TWCV）來評估此三種分群法（SOM,ASCA,IACA）

  10. Simulation Result

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