混合式進化演算法於微陣列資料分類法則探勘之研究

Using A Hybrid Meta-evolutionary Algorithm for Mining Classification Rules Through Microarray Data

尤婷藝(Ting-Yi Yu)

指導教授 ： 陳大正

國立虎尾科技大學/管理學院/資訊管理研究所/碩士(2010年)

https://doi.org/10.6827/NFU.2010.00010

摘要

隨著資訊技術的蓬勃發展，基因微陣列資料成為癌症分類研究中重要的研究領域。由於基因微陣列資料具有高維度基因屬性且樣本數少的特性，因而造成在分類時辨識度低，而且需要冗長的運算時間成本。因此，在面臨基因微陣列資料分類問題時，如何萃取出關鍵且具代表性的基因屬性以獲得較高的分類預測準確率並且有效的提升運算品質成為一項重要的研究議題。因此，本研究提出一個以基因演算法結合二元粒子群最佳化演算法之法則探勘模型，藉由混合式進化演算法在分類問題上進行樣本數值的評量，並同時萃取預測變數、相對應的隸屬函數及參數值之模糊分類法則，透過微陣列資料的屬性維度之調整及隸屬函數的選擇，僅需使用較少量的基因屬性即可達到高準確率的分類。此外，透過模糊法則可觀察出資料屬性與類別之間的相互關係。為了降低分類時所需的龐大運算，本研究結合了格網運算技術來有效降低分析運算所需耗費的時間成本，以建立高預測準確率之分類法則。將實驗結果與過去相關文獻中的方法以及商業探勘軟體進行比較，透過研究顯示本研究所提出的方法能獲得較佳的分類正確率並有效的降低運算的時間。

關鍵字

進化式演算法 ； 分類法則 ； 資料探勘 ； 基因微陣列資料

並列摘要

With the rapid development of information technology, microarray data is an important field of study for cancer research. However, microarray data is with high dimensional attributes and small sample size resulting in lengthy computation time and low classification accuracy. Due to gene microarray data classification issues, how to get more accurate prediction results with better quality becomes an important area of research. This thesis has proposed a hybrid evolutionary algorithm which combines a genetic algorithm and binary particle swarm optimization with fuzzy discriminate function. The proposed method is used to estimate the fitness value for classification, significant variables extraction, and parameters of fuzzy membership function in the meanwhile. Through the adjustment of the dimension of microarray data and the choice of membership function, fewer significantly characteristic attributes can reach high classification accuracy. Fuzzy rules can also be observed through data attributes and the relationship between categories. To reduce the vast computation time for classification process, this study integrates grid computing technology in the proposed approach. The experimental results show our proposed method can achieve higher classification accuracy and effectively reduces the computation time.

並列關鍵字

evolutionary algorithm ； classification rules ； data mining ； microarray data

參考文獻

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