计算机系统应用
計算機繫統應用
계산궤계통응용
APPLICATIONS OF THE COMPUTER SYSTEMS
2014年
10期
138-141
,共4页
兰远东%高蕾%曾少宁%曾树洪
蘭遠東%高蕾%曾少寧%曾樹洪
란원동%고뢰%증소저%증수홍
降维%半监督学习%局部保持%分类%机器学习
降維%半鑑督學習%跼部保持%分類%機器學習
강유%반감독학습%국부보지%분류%궤기학습
dimensionality reduction%semi supervised learning%local preserving%classification%machine learning
为了对高维数据进行降维处理，提出了半监督学习的边缘判别嵌入与局部保持的维度约简算法。通过最小化样本与其所属类别的中心点之间的距离，使得样本在投影子空间中能够保持其领域的拓扑结构；再通过最大化不同类别边缘间的距离，使得类别间的分离度在投影子空间中得到增强。实验结果表明：半监督边缘判别嵌入与局部保持的维度约简算法能够获得初始特征空间的较好的投影子空间。
為瞭對高維數據進行降維處理，提齣瞭半鑑督學習的邊緣判彆嵌入與跼部保持的維度約簡算法。通過最小化樣本與其所屬類彆的中心點之間的距離，使得樣本在投影子空間中能夠保持其領域的拓撲結構；再通過最大化不同類彆邊緣間的距離，使得類彆間的分離度在投影子空間中得到增彊。實驗結果錶明：半鑑督邊緣判彆嵌入與跼部保持的維度約簡算法能夠穫得初始特徵空間的較好的投影子空間。
위료대고유수거진행강유처리，제출료반감독학습적변연판별감입여국부보지적유도약간산법。통과최소화양본여기소속유별적중심점지간적거리，사득양본재투영자공간중능구보지기영역적탁복결구；재통과최대화불동유별변연간적거리，사득유별간적분리도재투영자공간중득도증강。실험결과표명：반감독변연판별감입여국부보지적유도약간산법능구획득초시특정공간적교호적투영자공간。
In order to reduce the dimension of high-dimensional data, raised edge semi-supervised marginal discriminant embedding and local preserving algorithm for dimensionality reduction is proposed. By minimizing the distance between sample and the center of its category, the local topology of samples is maintained in the projection subspace. And by maximizing the distance between the edges of different categories, the inter scatter of classes is increased in the projection subspace. Experimental results show that the dimensionality reduction algorithm of semi supervised marginal discriminant embedding and local preserving can get a better projection subspace of the initial feature space.
