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clean data造句

"clean data"是什么意思  
造句與例句手機(jī)版
  • Transformations modify , summarize , and clean data
    轉(zhuǎn)換修改、匯總和清除數(shù)據(jù)。
  • The data cleaning sample is a package that cleans data
    數(shù)據(jù)清除示例是一個(gè)清除數(shù)據(jù)的包。
  • The clean data transformer provides the following clean types that you can specify
    Clean data轉(zhuǎn)換器提供了下列可供指定的清理類型:
  • Another transformation cleans data by grouping values in a dataset that are similar
    另一種轉(zhuǎn)換通過將數(shù)據(jù)集中相似的值分組到一起來清理數(shù)據(jù)。
  • The clean data transformer operates on specified data columns of the source table that your step accesses
    Clean data轉(zhuǎn)換器操作源表中步驟所訪問的特定數(shù)據(jù)列。
  • A rules table designates the values that the clean data transformer will use during the find and replace process
    規(guī)則表指定clean data轉(zhuǎn)換在查找和替換過程中將使用的值。
  • Only the clean data is delivered to the browser , every malware is stopped before it gets saved on your pc
    只有安全的數(shù)據(jù)才可以傳送到瀏覽器,惡意軟件在到達(dá)計(jì)算機(jī)以前被阻止
  • The clean data transformer in db2 data warehouse center can be used for basic data verification purposes
    Db2 data warehouse center中的clean data轉(zhuǎn)換器可以用于基本的數(shù)據(jù)驗(yàn)證目的。
  • Performing business intelligence operations such as cleaning data , mining text , or running data mining prediction queries
    執(zhí)行商業(yè)智能操作,如清除數(shù)據(jù)、挖掘文本或運(yùn)行數(shù)據(jù)挖掘預(yù)測查詢。
  • Defines transaction context within services , allowing for clean data operations when multiple tasks are operating at the same time
    :在服務(wù)中定義事務(wù)上下文,允許在同時(shí)操作多項(xiàng)任務(wù)時(shí)清除數(shù)據(jù)操作。
  • It's difficult to see clean data in a sentence. 用clean data造句挺難的
  • Demonstrates how to run sql create table statements in a loop , evaluate and clean data values , and insert data into tables
    說明如何運(yùn)行循環(huán)中的sql create table語句,計(jì)算和清除數(shù)據(jù)值以及將數(shù)據(jù)插入表中。
  • The following transformations perform business intelligence operations such as cleaning data , mining text , and running data mining prediction queries
    下列轉(zhuǎn)換執(zhí)行商業(yè)智能操作,如清除數(shù)據(jù)、挖掘文本以及運(yùn)行數(shù)據(jù)挖掘預(yù)測查詢。
  • You can also use the clean data transformer to clean and standardize data values after loading or importing data as part of a process
    在將數(shù)據(jù)作為過程中一部分進(jìn)行裝入或?qū)胫?,您還可以使用clean data轉(zhuǎn)換器來清理和標(biāo)準(zhǔn)化數(shù)據(jù)值。
  • Using an integration services transformation , you can modify values in columns , look up values in tables , clean data , and aggregate column values
    通過使用integration services轉(zhuǎn)換,可以修改列中的值、查找表中的值、清理數(shù)據(jù)以及聚合列值。
  • You can use the clean data transformer in db2 warehouse center to perform basic cleaning , substitution , and mapping operations on source data
    您可以使用db2 warehouse center中的clean data轉(zhuǎn)換器來執(zhí)行源數(shù)據(jù)上的基本清理、替換和映射操作。
  • Demonstrates how to clean data by applying exact and fuzzy matching of new customers to existing customers , and how to identify duplicate customers by using fuzzy grouping
    說明如何對(duì)新客戶和現(xiàn)有客戶應(yīng)用完全匹配和模糊匹配,以及如何使用模糊分組標(biāo)識(shí)重復(fù)的客戶。
  • This ability to use both dynamic sql and sprocs with a clean data model layer is pretty powerful , and provides a great deal of flexibility when working on projects
    這種數(shù)據(jù)模型的既能調(diào)用動(dòng)態(tài)sql又能調(diào)用存儲(chǔ)過程能力是非常強(qiáng)大的,并且在對(duì)對(duì)象的操作上它提供了強(qiáng)大的靈活性。
  • You specify the replacement value in the properties notebook for the clean data transformer . you must specify a replacement value that is of the same data type as the source column
    您要在clean data轉(zhuǎn)換器的properties記事本中指定替換值,并且必須指定與源列數(shù)據(jù)類型相同的替換值。
  • An integration services package can also clean data by replacing the values in columns with values from a reference table , using either an exact lookup or fuzzy lookup to locate values in a reference table
    Integration services包還可以使用精確查找或模糊查找來找到引用表中的值,通過將列中的值替換為引用表中的值來清理數(shù)據(jù)。
  • The result shows that the efficiency and precision of prediction for clean data are satisfactory . although there are some errors in the prediction of noisy and chaotic data , the result is acceptable
    實(shí)驗(yàn)結(jié)果表明,當(dāng)數(shù)據(jù)無噪聲時(shí),預(yù)測效率與精度都非常高;在處理帶噪聲,并呈現(xiàn)混沌特性的數(shù)據(jù)時(shí),雖有一定的誤差,但預(yù)測結(jié)果還是在可以接受的范圍內(nèi)。
  • 更多造句:  1  2
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