classification analysis中文是什么意思

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中文翻譯
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分類(lèi)分析

classification n. 1.選別；分等，分級(jí)；分選。 2.【動(dòng)、植】分類(lèi)( ...
analysis n. (pl. -ses ) 1.分解，分析；【數(shù)學(xué)】解 ...
danac data analysis and classification 數(shù)據(jù)分析與分類(lèi)
multiple classification analysis 多重分類(lèi)分析
classification n. 1.選別；分等，分級(jí)；分選。 2.【動(dòng)、植】分類(lèi)(法)。〔分類(lèi)級(jí)別為： phylum 【動(dòng)物；動(dòng)物學(xué)】及 division 【植物；植物學(xué)】門(mén)，class 綱，order 目，family 科，genus 屬，species 種，variety 品種〕。 3.類(lèi)別；等級(jí)；(文件的)保密級(jí)。 a classification yard (車(chē)站的)調(diào)車(chē)場(chǎng)。
analysis n. (pl. -ses ) 1.分解，分析；【數(shù)學(xué)】解析。 2.梗概，要略。 3.〔美國(guó)〕用精神分析法治療(＝ psychoanalysis)。 in the last analysis= on (the last) analysis 歸根結(jié)底，總之。 under analysis 在精神分析治療下。
be analysis 損益分界分析,保本分析
in the analysis of 在對(duì)……進(jìn)行分析時(shí)
on analysis 經(jīng)分析后
analysis analysis 分析，解析
a broad classification 粗略的分類(lèi)
abbott classification 阿波特分類(lèi)法
abc classification abc分類(lèi)法; abc分類(lèi)管理; 分類(lèi)管理
account classification 會(huì)計(jì)科目表; 帳戶(hù)分類(lèi); 帳目分類(lèi)，會(huì)計(jì)科目分類(lèi)
accounting classification 會(huì)計(jì)分類(lèi); 會(huì)計(jì)科目分類(lèi)
activity classification 操作分類(lèi); 業(yè)務(wù)活動(dòng)分類(lèi); 作業(yè)分類(lèi)，業(yè)務(wù)分類(lèi)
administrative classification 行政管理類(lèi)別
agency classification 按部門(mén)分類(lèi)
agricultural classification 農(nóng)藝分類(lèi)
agroclimatic classification 農(nóng)業(yè)氣候分型
air classification 風(fēng)選; 空氣分級(jí); 空氣分類(lèi); 空氣風(fēng)力分級(jí); 空氣風(fēng)力分離; 氣力分選; 氣流分級(jí)
airflow classification 分流式分選
airmass classification 氣團(tuán)分級(jí); 氣團(tuán)分類(lèi)
algorithm classification 算法分類(lèi)
alphabetical classification 字母分類(lèi)法

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例句與用法

Style classification analysis of chinese mutual funds
中國(guó)證券投資基金風(fēng)格分類(lèi)研究
Gray system classification analysis and lake eutrophication assessment
灰色系統(tǒng)聚類(lèi)分析與湖泊富營(yíng)養(yǎng)程度評(píng)價(jià)
And effects on improving original inversion image are clear by associated use of post treatments , variance truncating , median filtering and classification analysis
依據(jù)模型參數(shù)方差向量，本文提出了方差截?cái)嗪筇幚矸椒ǎ⒔Y(jié)合中值濾波和聚類(lèi)分析，對(duì)原始反演圖像進(jìn)行去噪后處理，成效明顯。
It focuses on the classification analysis in terms of the content of nationalism , the geographic boundary of nationalism and the political orientation of nationalism ; part ii analyzes the major features of the contemporary nationalism
本文旨在嘗試在對(duì)民族主義進(jìn)行分類(lèi)、對(duì)民族主義在冷戰(zhàn)后的表現(xiàn)及民族主義泛起的原因進(jìn)行分析的基礎(chǔ)上，對(duì)全球化時(shí)代民族主義在新世紀(jì)的發(fā)展趨勢(shì)做初步的探討。
According to user ' s request of flexible query , finding rule through data , data visualizing , jjms applied descriptive data mining including olap , concept description and so on . it realized the function of basic analysis , classification analysis , related analysis , characteristic value analysis . the result show at the way of pivot table , pivot chart . it satisfied the user preferably
“交通部紀(jì)檢監(jiān)察統(tǒng)計(jì)分析系統(tǒng)”根據(jù)用戶(hù)提出的靈活統(tǒng)計(jì)、從數(shù)據(jù)中發(fā)現(xiàn)規(guī)律、直觀展現(xiàn)數(shù)據(jù)的需求，應(yīng)用olap 、概念描述等描述數(shù)據(jù)挖掘技術(shù)，實(shí)現(xiàn)了基本情況分析、分類(lèi)分析、動(dòng)態(tài)分析、關(guān)聯(lián)分析、特征值分析等一系列功能，以透視表、透視圖為主要的數(shù)據(jù)展現(xiàn)方式，較好的滿(mǎn)足了用戶(hù)的需求，得到了用戶(hù)的肯定。
The third part talks about the analysis and design of the business intelligence module which is a part of zhen xiang project , then explores the application of data mining to provide market basket analysis , customer classification analysis and other intelligent analyses . we research on how to provide intelligent analysis based on data mining for the enterprise in the e - commerce system
本文對(duì)振湘項(xiàng)目二期工程的商業(yè)智能分析子系統(tǒng)進(jìn)行了分析和設(shè)計(jì)，嘗試應(yīng)用數(shù)據(jù)挖掘來(lái)完成購(gòu)物籃分析、客戶(hù)細(xì)分等分析功能，并且對(duì)在電子商務(wù)系統(tǒng)中結(jié)合企業(yè)需求提供基于數(shù)據(jù)挖掘的智能分析服務(wù)進(jìn)行了有意義的研究探索。
Data mining is an important research subject in the field of information technology . it means a process of nontrivial extraction of implicit , previously unknown and potentially useful information from data in databases or datawarehouses . it involves such subject areas as database , artificial intelligence , machine learning and statistics . classification analysis is an important data mining problem
數(shù)據(jù)挖掘( datamining )是信息處理技術(shù)研究領(lǐng)域的一項(xiàng)重要課題。它是指從大型數(shù)據(jù)庫(kù)或數(shù)據(jù)倉(cāng)庫(kù)中提取隱含的、未知的、非平凡的以及有潛在應(yīng)用價(jià)值的信息或模式的過(guò)程。
This thesis expatiates on the state - of - the - art of dm technique , with emphasis on data mining algorithms such as clustering analysis , classification analysis , dependence analysis and statistical analysis . a comparative study of three popular dm tools ( ibm intelligent miner , spss clementine and sas enterprise miner ) is carried out . the future trends of dm technology are also revealed
論文闡述了數(shù)據(jù)挖掘技術(shù)在國(guó)內(nèi)外的研究現(xiàn)狀,對(duì)目前主要的數(shù)據(jù)挖掘算法如聚類(lèi)分析、分類(lèi)分析、相關(guān)分析和統(tǒng)計(jì)分析進(jìn)行了剖析,對(duì)當(dāng)前最為流行的數(shù)據(jù)挖掘工具ibmintelligentminer 、 spssclementine及sasenterpriseminer進(jìn)行比較分析,闡述了數(shù)據(jù)挖掘技術(shù)的未來(lái)發(fā)展趨勢(shì)。
The studying method of flora adopted by this thesis are follows : the statistics of the dominant families and genera , along with single families and genera , abundance index ( ai ) , similarity coefficient of genus ( scg ) , floristic spectrum analysis ( fsa ) , principal components analysis ( pca ) , as well as agglomerative classification analysis ( aca )
16 ；單種屬占總屬數(shù)的39 39 ，其種數(shù)僅占總種數(shù)的門(mén)26 ；而6個(gè)優(yōu)勢(shì)科中所含的種數(shù)占到總種數(shù)的903 ， 9個(gè)優(yōu)勢(shì)屬中所含的種數(shù)占總種數(shù)的47

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