頻繁模式 的英文怎麼說

中文拼音 [bīnfánmóshì]
頻繁模式 英文
frequent pattern
  • 頻 : Ⅰ形容詞（次數多） frequent Ⅱ副詞（屢次） frequently; repeatedly Ⅲ名詞1 [物理學] （物體每秒鐘振動...
  • 繁 : 繁名詞（姓氏） a surname
  • 模 : 模名詞1. （模子） mould; pattern; matrix 2. （姓氏） a surname
  • 式 : 名詞1 （樣式） type; style 2 （格式） pattern; form 3 （儀式; 典禮） ceremony; ritual 4 （自然科...
  • 頻繁 : frequently; often
  • 模式 : model; mode; pattern; type; schema
  1. In addition, comparing to direct using fp _ growth algorithms, this algorithm has no need to expand negative item to original database, and construc or destruct additional data structures, which only make some changes on the original frequent pattern tree, so it has certain advantages in time and space costs

    除此之外，該演算法與直接使用fp _ growth演算法挖掘含負項目的頻繁項集演算法相比，無需對原始數據庫進行負項目的擴展，也不用再構造並銷毀額外的數據結構，只需在原始的頻繁模式樹上修改，在時間和空間的開銷上都具有一定的優勢。
  2. With the development of computer applications, the requirements of software projects become more complicated and change more frequently. at the same time, more semifinished products are produced and their relationships become more complex. the development pattern of the project has already been changed into scale, group developing from the craft workshop - based developing in the past

    隨著計算機應用的深入，軟體項目的需求日益復雜且變更頻繁，軟體中間產品越來越多並且關系復雜，項目的開發模式己經由昔日的手工作坊式的開發轉變為規模化、團隊式的開發。
  3. Provide an accessor for their connection ; however, application servers and web application frameworks frequently use the decorator pattern to wrap jdbc connections

    為它們的連接提供了存取器；但是，應用程序服務器和web應用程序框架頻繁地使用修飾器模式包裝jdbc連接。
  4. A popular solution toimprove the speed and scalability of the association rule mining is todo the algorithm on a random sample instead of the entire database. buthow to effectively define and efficiently estimate the degree of errorwith respect to the outcome of the algorithm, and how to determine the samplesize needed are entangling researches until now. in this paper, an effective and efficient algorithm is given based on the pac probably approximate correct learning theory to measure and estimatesample error

    關聯規則挖掘作為數據挖掘的核心任務之一，由於其任務本身的復雜性通常需要多次整個掃描數據庫才能完成挖掘任務且頻繁模式可能產生組合爆炸，使得從原始的大規模數據集上抽取一部分樣本，在其上尋找用戶感興趣的近似規則成為目前提高演算法效率和可擴展性的一種簡單有效的現實可行方法之一。
  5. We devise an algorithm that antomatically constructs temporal and statistical features according to the semantics of the patterns. in the end, the effectiveness of this method is evaluated in an experiment

    我們還設計了一個統計特徵構造程序，它根據從審計數據中產生的頻繁模式的語法自動地構造臨時性的、統計的特徵。
  6. Paper presentes a new algorithm of mining frequent item sets with negative items

    論文提出一種新的挖掘含負項目的頻繁項集演算法，即基於頻繁模式樹的演算法。
  7. We develop an simple encoding algorithm so that frequent patterns can be easily analyzed, and compared

    我們設計了一個簡單的編碼演算法以便容易地分析和比較頻繁模式。
  8. All urge people to put more and more attentions to the frequent pattern mining in graphs

    同時，隨著各種新應用的不斷推出，人們將注意力逐步向圖中的頻繁模式的產生問題轉移。
  9. Frequent pattern mining technology in data mining is for mining characteristic patterns with frequent occurrences among data

    數據挖掘中的頻繁模式挖掘技術專注于發現數據中頻繁出現的特徵模式。
  10. When there are a great many of items and transactions in the database, frequent - pattern growth algorithm needs more additional computer memory, which may cause the lack of memory

    當數據庫中的項目數目較大且事務數量巨大時，頻繁模式增長演算法內存開銷很大，可能導致內存空間不足的現象。
  11. Next, after near 10 years research and development, the most essential phase in association rules mining, frequent pattern acquirement, and its techniques have been improved dramatically

    其次，在經歷了近10年的發展以後，關聯規則挖掘中至關重要的頻繁模式獲取技術得到了很大的發展。
  12. This paper discusses and proposes a new simple algorithm of discovering all the frequent itemsets in relational database by the standard sql. experiments which provee the algorithm is high effective

    摘要利用標準sql語言提出了一種在關系數據庫中挖掘頻繁模式的簡易演算法。實驗證明該演算法具有較高的效率。
  13. The work in the dissertation is strictly bounded in such field by following the two phases, frequent pattern acquirement and rules generation, to deep into the extended research step by step

    本文的工作在關聯規則挖掘的范疇以內，根據關聯規則的生成的二個主要階段：頻繁模式的獲取和關聯規則的生成進行了深入的拓展性研究。
  14. While most of these algorithms are based on apriori line, will generate a huge number of candidate itemsets, need multiple scans over database, and maintain a big hash tree, so the time and space complexity is too high

    這些演算法大多基於apriori演算法，在挖掘頻繁模式時需要產生大量候選項集，多次掃描數據庫和維護一棵很大的hash樹，時空復雜度過高。
  15. The algorithm is based on the frequent pattern tree, which uses for reference a compressed storage data structure i. e. frequent pattern tree of fp _ growth algorithm. it mines frequent item sets with negative items through extending frequent patterns on the tree

    該演算法借用fp _ growth演算法中頻繁模式樹這種壓縮存儲事務的數據結構，通過頻繁模式樹進行模式擴展，挖掘含負項目的頻繁項集。
  16. Using this method, raw audit data is first preprocessed into records with a set of basic features. data mining algorithms are then applied to compute the frequent patterns from records, whitch are automatically analyzed to generate an additional set of features for intrusion detection purposes

    本方法中，首先把原始審計記錄處理成包含基本特徵的連接記錄，然後應用數據挖掘演算法計算連接記錄中的頻繁模式，並從頻繁模式中自動生成入侵檢測的附加特徵。
  17. Raw audit data of the system or network is first preprocessed into records with a set of basic features. then the association algorithms and the frequent algorithms are used to compute the frequent patterns from the records, which are the basis for building or selecting system features

    系統中各代理相互協作，對系統或者網路的原始審計數據進行預處理生成包含基本特徵的連接記錄；利用數據挖掘中的關聯規則挖掘演算法和頻繁序列規則挖掘演算法，得到系統事件在屬性間和時間序列上的頻繁模式。
  18. This paper discussed the clustering algorithms based on the longest frequent closed itemsets using frequent - pattern tree, concluded that in some situation it is inapproriate to using this technique to classifing data in data mining

    摘要針對採用頻繁模式樹構造的最長頻繁閉項集的聚類演算法，提出該演算法在一些特殊環境下可能產生的誤差，因而建議在一些應用情況下，不宜採用該演算法進行數據挖掘中的數據分類。
  19. The paper summarizes the history of frequent pattern mining technology and the development of frequent sub tree mining algorithms ; introduces the main methods of rna secondary structure prediction ; analyzes the deficiency of the applications of data mining in bioinformatics

    本文首先概括了頻繁模式挖掘技術及頻繁子樹挖掘演算法的現狀，介紹了rna二級結構預測的主要方法，探討了目前數據挖掘技術應用於生物數據所存在的問題。
  20. A few classic association rule extracting algorithms are deeply discussed. in order to resolve frequent pattern mining problem efficiently, redundant operation and temporary data in fp - growth algorithm are analyzed, data structures, fpr - tree and fpr - list, are imported, the method of conditional pattern base generation and storage in fp - growth algorithm is improved, and a new fprsg algorithm is presented

    為解決頻繁模式挖掘問題，本文通過分析fp - growth演算法中包含的冗餘操作，引入數據結構fp參考樹/表，改變fp - growth演算法中條件模式基的存儲和生成方式，提出了新的fprsg演算法，高效地解決了頻繁模式挖掘問題。
分享友人
分享到 Line

分享到臉書