计算机应用与软件
計算機應用與軟件
계산궤응용여연건
Computer Applications and Software
2015年
9期
175-180
,共6页
多流形学习%线性判别分析%局部保持投影%特征提取
多流形學習%線性判彆分析%跼部保持投影%特徵提取
다류형학습%선성판별분석%국부보지투영%특정제취
Multi-manifold learning%Linear discriminant analysis%Locality preserving projection%Feature extraction
传统的多流形判别分析（MMDA）方法要求每类样本数目必须相同，这在实际中往往很难满足，因此限制了它的应用。针对此问题，提出一种改进的多流形判别分析（IMMDA）方法。该方法去除了MMDA中的限制条件，用类内图和类间图来描述类内紧凑度和类间离散度，类内图可以代表子流形信息，类间图可以代表多流形信息，从而更好地实现分类。在FERET、ORL人脸库及UCI数据集上的实验证明了该方法的有效性。相比其他几种子空间学习方法，该方法取得了更好的识别效果。
傳統的多流形判彆分析（MMDA）方法要求每類樣本數目必鬚相同，這在實際中往往很難滿足，因此限製瞭它的應用。針對此問題，提齣一種改進的多流形判彆分析（IMMDA）方法。該方法去除瞭MMDA中的限製條件，用類內圖和類間圖來描述類內緊湊度和類間離散度，類內圖可以代錶子流形信息，類間圖可以代錶多流形信息，從而更好地實現分類。在FERET、ORL人臉庫及UCI數據集上的實驗證明瞭該方法的有效性。相比其他幾種子空間學習方法，該方法取得瞭更好的識彆效果。
전통적다류형판별분석（MMDA）방법요구매류양본수목필수상동，저재실제중왕왕흔난만족，인차한제료타적응용。침대차문제，제출일충개진적다류형판별분석（IMMDA）방법。해방법거제료MMDA중적한제조건，용류내도화류간도래묘술류내긴주도화류간리산도，류내도가이대표자류형신식，류간도가이대표다류형신식，종이경호지실현분류。재FERET、ORL인검고급UCI수거집상적실험증명료해방법적유효성。상비기타궤충자공간학습방법，해방법취득료경호적식별효과。
Traditional multi-manifold discriminant analysis (MMDA)usually requires the number of samples in each class must be the identical,which is hard to be satisfied in real-world applications,so its application is restrained.To tackle this problem,we propose an improved multi-manifold discriminant analysis (IMMDA)method.IMMDA removes the limitation in MMDA.It uses within-class graph and between-class graph to describe the within-class compactness and the between-class separability.In addition,the within-class graph can represent the sub-manifold information, while the between-class graph can represent the multi-manifold information, so that better classification is achieved.The experiments carried out on FERET,ORL and the UCI datasets proves the effectiveness of IMMDA.It is superior to other learning methods in terms of the recognition performance.
