classification n. 1.選別;分等,分級;分選。 2.【動、植】分類(法)。 〔分類級別為: phylum 【動物;動物學】及 division 【植物;植物學】門,class 綱,order 目,family 科,genus 屬,species 種,variety 品種〕。 3.類別;等級;(文件的)保密級。 a classification yard (車站的)調車場。
analysis n. (pl. -ses ) 1.分解,分析;【數學】解析。 2.梗概,要略。 3.〔美國〕用精神分析法治療(= psychoanalysis)。 in the last analysis= on (the last) analysis 歸根結底,總之。 under analysis 在精神分析治療下。
Style classification analysis of chinese mutual funds 中國證券投資基金風格分類研究
Gray system classification analysis and lake eutrophication assessment 灰色系統聚類分析與湖泊富營養程度評價
And effects on improving original inversion image are clear by associated use of post treatments , variance truncating , median filtering and classification analysis 依據模型參數方差向量,本文提出了方差截斷后處理方法,并結合中值濾波和聚類分析,對原始反演圖像進行去噪后處理,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 本文旨在嘗試在對民族主義進行分類、對民族主義在冷戰后的表現及民族主義泛起的原因進行分析的基礎上,對全球化時代民族主義在新世紀的發展趨勢做初步的探討。
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 “交通部紀檢監察統計分析系統”根據用戶提出的靈活統計、從數據中發現規律、直觀展現數據的需求,應用olap 、概念描述等描述數據挖掘技術,實現了基本情況分析、分類分析、動態分析、關聯分析、特征值分析等一系列功能,以透視表、透視圖為主要的數據展現方式,較好的滿足了用戶的需求,得到了用戶的肯定。
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 本文對振湘項目二期工程的商業智能分析子系統進行了分析和設計,嘗試應用數據挖掘來完成購物籃分析、客戶細分等分析功能,并且對在電子商務系統中結合企業需求提供基于數據挖掘的智能分析服務進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 數據挖掘( datamining )是信息處理技術研究領域的一項重要課題。它是指從大型數據庫或數據倉庫中提取隱含的、未知的、非平凡的以及有潛在應用價值的信息或模式的過程。
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 論文闡述了數據挖掘技術在國內外的研究現狀,對目前主要的數據挖掘算法如聚類分析、分類分析、相關分析和統計分析進行了剖析,對當前最為流行的數據挖掘工具ibmintelligentminer 、 spssclementine及sasenterpriseminer進行比較分析,闡述了數據挖掘技術的未來發展趨勢。
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 ;單種屬占總屬數的39 39 ,其種數僅占總種數的門26 ;而6個優勢科中所含的種數占到總種數的903 , 9個優勢屬中所含的種數占總種數的47