挖掘模型 的英文怎麼說

中文拼音 [wājuémóxíng]
挖掘模型 英文
mining model
  • 挖 : 動詞（用工具或手從物體的表面向里掘取） dig; excavate; scoop
  • 掘 : 動詞（刨; 挖） dig
  • 模 : 模名詞1. （模子） mould; pattern; matrix 2. （姓氏） a surname
  • 挖掘 : excavate; unearth; dig; tap; grub; hoe; grave
  • 模型 : 1 （仿製實物） model; pattern 2 （制砂型的工具） mould; pattern3 （模子） model set; mould patter...
  1. Configuring the data mining model training destination

    配置數據挖掘模型定型目標
  2. You must reprocess the structure, and the associated mining models

    必須重新處理結構和關聯的挖掘模型。
  3. And then it emphasizes the structure model and the process of data warehouse, the ways of extracting data from operation model and guiding into the data warehouse, the realization techniques of dealing with data synthetically, as well as the mechanism of how to superadd the upper data into the data warehouse, and introduces the realization techniques of the mining model of association rule, the apriori and the fp - growth arithmetic particularly

    接著重點討論了數據倉庫的構建模型和構建過程，從操作型環境抽取數據並導入數據倉庫方法，對數據進行綜合處理的實現技術，以及後期數據如何追加到數據倉庫的機制，並詳細介紹了關聯規則挖掘模型， apriori演算法，和fp - growth演算法的實現技術。
  4. Mining models can be applied to specific business scenarios, such as

    挖掘模型可以應用於特定的業務方案，例如：
  5. Then you select an attribute to use as the key, or case key, of the mining model

    最後，選擇要用作挖掘模型的鍵（即「事例鍵」 ）的屬性
  6. In a restore operation, a file that is used during the undo phase to hold a " copy - on - write " pre - image of pages that are to be modified

    例如，數據挖掘模型可以指定進程的輸入、輸出、演算法及其他屬性，並保存定型活動期間收集的信息，例如，決策樹。
  7. The paper states the concept and theoretical basis of the data mining and knowledge discovery ( dmkd ) theory. it also deeply studies dmkd model that is appropriate to present chinese enterprise via the analysis of present popular dmkd models

    本文闡述了數據挖掘與知識發現（ dmkd ）的定義及所涉及到的基礎理論知識，對當前比較成功的數據挖掘模型進行了分析對比，探討了適合我國企業現狀的數據挖掘模型。
  8. With drillthrough clause enables drill through on the new mining model

    子句可以對新挖掘模型進行鉆取。
  9. The paper puts forward the model of reference about common corporations and detailed designs based on dw ' s requirements analysis, then discusses that how a corporation builds the dws ( data warehouse system ). this paper ' s main breakthrough lies on : in the information condition of national corporations, how to improve the decision - making ability of corporation by dw technology ; bringing forward the model of reference about common corporation ; constructing the dm model to control the quality of products

    在數據倉庫需求分析的基礎上，提出了數據倉庫系統建設的總體框架和詳細設計，然後論述了企業如何進行數據倉庫系統構建。本文的主要創新點在於：在國內企業目前的信息環境下，如何結合數據倉庫技術提高企業的決策能力，提出了一般企業的參照模型；在數據挖掘方面，提出了一個用以指導產品質量控制的數據挖掘模型。
  10. The data mining extensions language provides statements that you can use to create, train, and use data mining models

    數據挖掘擴展插件（ dmx ）語言提供了一些語句，您可以使用這些語句創建、定型和使用數據挖掘模型。
  11. The paper, in order to support for alteration of enterprise data analysis requirements, provides a kind of adaptive online analysis processing and data mining model ( abbreviated dolam ), its logic structure, system frame and physical structure are presented, which enhances hominine direction and controlling mechanism, embodying in such aspects as query - driven, fuzzy data mining and dynamic interactive ability etc. the paper offers design and implementation blue print of the core of dolam - - data warehouse management tool, olap tool and summarysql tool, now, they are running in dalian international cooperation ( group ) stock ltd and have gained good effect

    四、決策敏捷依賴于dss的柔性，為增強dss的柔性，本文提出一種具有可適應的聯機分析挖掘模型dolam ，設計了它的邏輯結構、體系結構和物理實現結構。該模型加強了人的導向和控制機制，體現在查詢驅動、模糊挖掘、動態交互方面。本文給出了dolam的核心部分?數據倉庫管理工具、 olap工具、 summarysql模糊查詢挖掘工具的具體設計和實現方案，並運用它于大連國際合作（集團）股份有限公司的決策支持實踐中，取得了較好的應用效果。
  12. Lesson 1 : creating the market basket mining structure

    第1課：創建市場籃挖掘模型
  13. We also build a series of models, including grey association model, grey - cluster model, grey prediction model, grey - neural - network model, grey - markoff model, grey - sequence model, etc. besides these, the author also apply these models in securities basic analysis and technological analysis

    這些模型包括灰關聯模型、灰聚類模型、灰預測模型、灰神經網路模型、灰馬爾可夫模型、灰序列模型、增長率和發展態勢挖掘模型等等。除此之外，作者還將這些模型應用於證券分析領域，分別在證券分析領域的基本分析方面和技術分析方面做了卓有成效的實證應用研究。
  14. Creating a sequence clustering mining model structure data mining tutorial

    >創建順序分析和聚類分析挖掘模型結構（數據挖掘教程）
  15. With im modeling, an sql job can be scheduled to mine the data and update the mining model without needing highly skilled data miners

    使用im modeling ，可以計劃sql作業來挖掘數據和更新挖掘模型，而無需高技術的數據挖掘器。
  16. Analysis services provides several options for processing mining model objects, including the ability to control which objects are processed and how they are processed

    Analysis services提供了數個用於處理挖掘模型對象的選項，其中包括控制處理哪些對象以及如何處理這些對象的功能。
  17. You could then build a mining model that relates demographics to how much money a customer spends in a store

    然後，您可以生成一個挖掘模型，該模型可將人口統計信息與某位客戶在商店中的消費金額關聯起來。
  18. A mining structure defines the data domain from which mining models are built

    挖掘結構定義基於其生成挖掘模型的數據域。
  19. Meanwhile, it is not confined in one area when developed for the second time, and by analyzing special domain data, the modal can be applied in the industries of banking, insurance, meteorology, and so on

    同時， sm miner挖掘模型在h次開發上並不受行業限制，通過分析具體的行業領域數據，本模型完全可以應用到銀行、保險、氣象等其它行業中。
  20. This tutorial walks you through scenarios for targeted mailing, forecasting, market basket analysis, and sequence clustering, to demonstrate how to use the data mining algorithms, mining model viewers, and data mining tools that are included in microsoft sql server 2005 analysis services ssas

    本教程將指導您演練目標郵件、預測、購物籃分析以及順序分析和聚類分析等方案，闡釋如何使用microsoft sql server 2005 analysis services （ ssas ）提供的數據挖掘演算法、挖掘模型查看器以及數據挖掘工具。
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