例句與造句

1. Based on unsupervised learning , sparse coding is suitable to describe images with non - gaussian distribution and can get rid of the high order redundancy among the image pixels . since the basis function of sparse coding has build - in clustering property , it increases the inter - class variations of the features
   稀疏編碼是一種基于非監(jiān)督學(xué)習(xí)的算法，它適合描述具有非高斯分布的數(shù)據(jù)對象，能夠有效地消除圖像象素點(diǎn)之間的冗余，并具有內(nèi)在的聚類特性。
2. Based on this kind of relations between the topological structures and the content distributions we study the web modelling , community identification and some related application problems in detail : first , after some existed characteristics of the web topology are verified , some new characteristics are discovered : the high clustering property in micro - topology ( high average gathering coefficient ) , the obvious mapping relation between the topological struture and the content in micro - level 、 linear irrelevant between the degree distribution of network nodes and the relative degree distribution of contents etc . then after analysis the topology of the complex network and the network modeling , the muti - scale determinism is proposed , especially for the information network a web evolvement model ( prcp model ) that fused the node authority and the node correlation is proposed . the model deduction , evolving learning verification and large scale experiment proof indicate that the model can explain the micro - topology centralizing phenomena , can imitate the mapping relation between the network connecting distribution and network content relative distribution and also can predict the mapping relation between the topology clustering and content clustering
   本文在詳細(xì)觀察了web網(wǎng)絡(luò)的拓?fù)浣Y(jié)構(gòu)特征以及拓?fù)浣Y(jié)構(gòu)與內(nèi)容分布相互關(guān)系的基礎(chǔ)上,以信息網(wǎng)絡(luò)的物理連接拓?fù)浣Y(jié)構(gòu)與節(jié)點(diǎn)內(nèi)容相關(guān)度分布之間的相互關(guān)系為主線,從網(wǎng)絡(luò)特征、網(wǎng)絡(luò)建模、社區(qū)分析及相關(guān)應(yīng)用方面問題進(jìn)行了深入細(xì)致地探討:首先在驗(yàn)證了前人提出的web網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)特征基礎(chǔ)上,進(jìn)一步發(fā)現(xiàn)了信息網(wǎng)絡(luò)所具有的一些新特征: 1 )網(wǎng)絡(luò)微觀顆粒度的拓?fù)浣Y(jié)構(gòu)聚團(tuán)與內(nèi)容聚團(tuán)存在明顯的映射關(guān)系,具體包括節(jié)點(diǎn)之間的物理連邊概率與節(jié)點(diǎn)之間的內(nèi)容相關(guān)度成指數(shù)比例關(guān)系、節(jié)點(diǎn)形成三角形拓?fù)浣Y(jié)構(gòu)的概率與節(jié)點(diǎn)內(nèi)容相關(guān)緊密程度之間同樣具有一種指數(shù)比例關(guān)系; 2 )網(wǎng)絡(luò)節(jié)點(diǎn)連接度整體分布與節(jié)點(diǎn)內(nèi)容相關(guān)度整體分布是線性無關(guān)的; 3 )網(wǎng)絡(luò)微觀拓?fù)浣Y(jié)構(gòu)中的存在很強(qiáng)的集聚性(平均聚團(tuán)系數(shù)很高) 。
3. Based on the clustering property of the basis function of sparse coding , a basis function initialization method using fuzzy c mean algorithm is proposed to help the energy function of sparse coding to converge to a better local minimum for recognition . experimental results show that the classification and the sparseness of the features are both improved
   經(jīng)過模糊c均值聚類初始化后的基函數(shù)能夠讓稀疏編碼的能量函數(shù)收斂到一個(gè)更有利于識(shí)別的局部最小點(diǎn)，試驗(yàn)結(jié)果表明特征的分類性和稀疏性都得到了提高。
4. It's difficult to find cluster property in a sentence. 用cluster property造句挺難的