√在线天堂中文最新版网,97se亚洲综合色区,国产成人av免费网址,国产成人av在线影院无毒,成人做爰100部片

當(dāng)前位置: 在線翻譯 > 英語(yǔ)翻譯 > 多值屬性
ONOFF
劃詞翻譯
導(dǎo)航
建議反饋
詞典App

多值屬性的英文

  • multiple-valued attribute

"查查詞典"手機(jī)版

千萬(wàn)人都在用的超大詞匯詞典翻譯APP

  • 例句與用法
  • Multi - valued attributes i . e . those declared with the
    多值屬性例如那些使用
  • You can perform an action whenever an element is deleted from a multi - valued attribute by specifying a delete trigger , like this
    當(dāng)一個(gè)成員從多值屬性中被刪除時(shí),我們可以定義一個(gè)刪除觸發(fā)器:
  • You can perform an action whenever the value of a single - valued attribute or an element of a multi - valued attribute is replaced , like this
    當(dāng)一個(gè)單值的屬性值或者多值屬性的成員被替換時(shí),我們可以定義一個(gè)替換觸發(fā)器:
  • If this flag is not present , all of the values , up to a server - specified limit , in a multi - valued attribute are returned when any value changes
    如果沒(méi)有此標(biāo)志,則當(dāng)任何值發(fā)生更改時(shí),將返回多值屬性中的所有值(最多到服務(wù)器指定的限制) 。
  • The aim which rough set theory study is a aim set that is described by a muti - value attribution . for every aim and its attribution , there has a value as its described charter aim , attribution and its described charter are the three basic factors to expression decision problems
    Rough集的研究對(duì)象是由一個(gè)多值屬性(特征,癥狀,特性)集合描述的一個(gè)對(duì)象集合,對(duì)于每個(gè)對(duì)象及其屬性都有一個(gè)值作為其描述符號(hào),對(duì)象,屬性和描述符是表達(dá)決策問(wèn)題的3個(gè)基本要素。
  • This part put forward the system conception of kdd and the apriori algorithm . then evolved the create - frequent - set algorithm which was fit for the freight agent management system . because of the shortage of efficiency , 1 improved the algorithm . because some of the items were not boolean variables , 1 need the quantitaitve attributes association rules discovering algorithm . in general , there had the levels among the items , so multilevel association rules existed . after perfecting the algorithmic need interpret and evaluate the knowledge . in the end , 1 discussed the privacy and security of kdd . the fifth part described the future problems and prospect
    第四章是論文的主體,著重介紹知識(shí)發(fā)現(xiàn)的全過(guò)程,按照semma方法論首先進(jìn)行數(shù)據(jù)準(zhǔn)備,然后進(jìn)入數(shù)據(jù)挖掘階段,提出知識(shí)發(fā)現(xiàn)的概念體系和公認(rèn)的apriori算法,從該算法演變出適合于貨代管理系統(tǒng)的生成頻繁項(xiàng)目集的算法;因?yàn)樵趯?shí)際應(yīng)用中存在效率上的不足,因此進(jìn)一步地提出了改進(jìn)方案;在事務(wù)處理中各個(gè)項(xiàng)目并不都是布爾型變量,因此需要特定的針對(duì)多值屬性的關(guān)聯(lián)規(guī)則發(fā)現(xiàn)算法;通常情況下,項(xiàng)目之間存在有層次關(guān)系,因此多層次關(guān)聯(lián)規(guī)則的發(fā)現(xiàn)普遍存在;算法完善并運(yùn)行后需要對(duì)發(fā)現(xiàn)的知識(shí)進(jìn)行解釋和評(píng)估;本章的最后討論了知識(shí)發(fā)現(xiàn)的私有性和安全性問(wèn)題;第五章講述有待解決的問(wèn)題和發(fā)展前景。
  • The decision tree had a lot of algorithms , this paper focus on the optimization of fast classification in the face of n - value attribute of id3 algorithm which had parameters of user ' s interest . on the basis of avoiding the weak relevant attribute of n - value covered the worth strong relevant attribute , simplify complexity of the original algorithm and code cost through the mathematics tool , thus raise the speed of operation while using this algorithm , and lower costs in thrift as much as possible , to raise the efficiency
    決策樹學(xué)習(xí)有很多算法,本文著重研究了對(duì)引入用戶興趣度參數(shù)的id3算法在面對(duì)多值屬性時(shí)的快速分類的優(yōu)化,在避免了多值弱相關(guān)屬性覆蓋少值強(qiáng)相關(guān)屬性的基礎(chǔ)上,通過(guò)數(shù)學(xué)工具簡(jiǎn)化原算法的復(fù)雜度和編碼代價(jià),從而提高使用該算法時(shí)的運(yùn)算速度,盡量多的節(jié)約計(jì)算時(shí)間,從而達(dá)到降低成本的,提高效率的目的。
  • The first chapter in this paper provides a survey of data mining technology , and explains basic concepts , function and the whole framework of data mining and difficulties in developing and some future directions in association rule generation ; the second chapter introduce the basic concepts , brings forward a classification of association rule ; the third chapter give a deep research on algorithms of every kind of association rule , include mining single - dimensional signal - level association rule and multidimensional multilevel association rule , it describes these algorithm , point out some method to optimize this algorithm and test its quality with experiments ; the fourth and fifth chapter introduce the designs about association rule mining system basing on relation database visual foxpro in detail : according to system frame of the association rule mining , actualize a new mining algorithms and analyses every function module of program , at last further analyses the left problems in designs
    本論文第一部分對(duì)數(shù)據(jù)挖掘技術(shù)進(jìn)行了總體介紹,說(shuō)明了基本概念、功能和系統(tǒng)總體框圖以及發(fā)展中的難點(diǎn)和研究方面;第二章對(duì)關(guān)聯(lián)規(guī)則基本概念的進(jìn)行了介紹,提出了關(guān)聯(lián)規(guī)則的分類方法;第三章探討了挖掘各種關(guān)聯(lián)規(guī)則的算法,從挖掘單維單層布爾關(guān)規(guī)則的經(jīng)典的apriori開始,分析了挖掘單維、多層關(guān)聯(lián)規(guī)則的算法,多維關(guān)聯(lián)規(guī)則的算法到多維多值屬性關(guān)聯(lián)規(guī)則的算法。文中提出算法優(yōu)化方法,并對(duì)其性能進(jìn)行了實(shí)驗(yàn)測(cè)試;第四部分、第五部分詳細(xì)介紹了基于關(guān)系型數(shù)據(jù)庫(kù)的關(guān)聯(lián)規(guī)則挖掘系統(tǒng)的設(shè)計(jì)構(gòu)思,根據(jù)關(guān)聯(lián)規(guī)則挖掘系統(tǒng)結(jié)構(gòu)框架,實(shí)現(xiàn)了基于visualfoxpro的關(guān)聯(lián)規(guī)則挖掘系統(tǒng),其于采用了一個(gè)新型的基于關(guān)系數(shù)據(jù)庫(kù)的關(guān)聯(lián)規(guī)則挖掘算法,提高了挖掘效率,并詳細(xì)分析了程序設(shè)計(jì)的各個(gè)功能模塊,最后就設(shè)計(jì)中遺留的問(wèn)題進(jìn)行了進(jìn)一步的分析。
  • 推薦英語(yǔ)閱讀
多值屬性的英文翻譯,多值屬性英文怎么說(shuō),怎么用英語(yǔ)翻譯多值屬性,多值屬性的英文意思,多值屬性的英文,多值屬性 meaning in English多值屬性的英文,多值屬性怎么讀,發(fā)音,例句,用法和解釋由查查在線詞典提供,版權(quán)所有違者必究。

說(shuō)出您的建議或使用心得