貝葉斯分類器 的英文怎麼說

中文拼音 [bèiyèsīfēnlèiqì]
貝葉斯分類器 英文
bayes classifier
  • 貝 : 名詞1 [動物學] （蛤螺等有殼軟體動物的統稱） cowry; cowrie; shellfis 2 （古代用貝殼做的貨幣） cowr...
  • 斯 : Ⅰ名詞（古代驅疫時用的面具） an ancient maskⅡ形容詞[書面語] （醜陋） ugly
  • 分 : 分Ⅰ名詞1. （成分） component 2. （職責和權利的限度） what is within one's duty or rights Ⅱ同 「份」Ⅲ動詞[書面語] （料想） judge
  • 類 : Ⅰ名1 （許多相似或相同的事物的綜合; 種類） class; category; kind; type 2 （姓氏） a surname Ⅱ動詞...
  • 器 : 名詞1. （器具） implement; utensil; ware 2. （器官） organ 3. （度量; 才能） capacity; talent 4. （姓氏） a surname
  • 貝葉 : （印度貝多羅 pattra 樹的葉子, 古代印度人用以寫佛經） pattra leaves
  1. Research for the classifiers based on bayesian networks

    基於貝葉斯網路的分類器研究
  2. Author develop three text dassiliers lilie naive - bayes classifier, k nearest neighbor classifier and svm classifier. furthermore, including the three classifiers, one text categorisation system is built up, and it has high prachcability

    作者採用三個模型，實現了樸素貝葉斯分類器、 k近鄰分類器和支持向量機分類器三個中文文本分類器，集成了一個實用性較強的實驗系統。
  3. Monte carlo is a method that approximately solves mathematic or physical problems by statistical sampling theory. when comes to bayesian classification, it firstly gets the conditional probability distribution of the unlabelled classes based on the known prior probability. then, it uses some kind of sampler to get the stochastic data that satisfy the distribution as noted just before one by one

    蒙特卡羅是一種採用統計抽樣理論近似求解數學或物理問題的方法，它在用於解決貝葉斯分類時，首先根據已知的先驗概率獲得各個類標號未知類的條件概率分佈，然後利用某種抽樣器，分別得到滿足這些條件分佈的隨機數據，最後統計這些隨機數據，就可以得到各個類標號未知類的后驗概率分佈。
  4. In tcm this pattern is called pair of medicine, and it can be resolved by frequent pattern mining. the symptom complex diagnose can be treated as a bayesian training and a bayesian classification on large clinical database cases. the critical step to resolve the chinese prescription compounding is to build an appropriate model to express the progress of it

    中藥知識發現集中在發現常用的單味藥合用模式，在中醫術語中稱之為藥對，這可以用高頻集發現來解決；中醫癥候診斷可以看成是在大量臨床案例庫上的貝葉斯訓練器和分類器；解決方劑配伍問題的關鍵是建立起一個合適的配伍計算機模型。
  5. 3 ) we construct the privacy preserving naive bayesian classifier

    3 ）構造了保持隱私的樸素貝葉斯分類器。
  6. Research on the method of processing empty value based on generalized naive bayes classifiers

    基於廣義樸素貝葉斯分類器的空值處理方法
  7. Because of ineffectiveness of naive bayes model for text classification, this thesis proposed integrating boosting theory of machine learning in classification process, boost naive bayes categorization model through many times training. improved by experiments, mutual information and naive bayes integrated with boosting bring very good precision, recall, and f1 score

    鑒于樸素貝葉斯的分類效果不佳，本論文又提出將機器學習中的boosting思想結合到樸素貝葉斯的分類模型中，對樸素貝葉斯模型進行提升，實驗證明，改進的互信息和給合了boosting思想的樸素貝葉斯分類模型均產生良好的分類效果?分準率、分全率及f1值。
  8. The oblivious polynomial evaluation protocol will be used many times in our privacy preserving naive bayesian classifier, so its efficiency is important to the solution

    健忘多項式計算協議在保持隱私的樸素貝葉斯分類器協議中多次用到，因此協議的效率是一個需要關心的問題。
  9. Theoretical analyses and experimental results demonstrate that this method is very effective. also, bayesian classifier, subspace method and ann are summarized in this chapter. they can be used for the next research

    本章還對貝葉斯分類器，子空間模式識別和人工神經網路在字元識別中的應用進行了總結，可作為進一步研究的基礎。
  10. By constructing two secure posterior probability evaluation protocols to deal with discrete and numeric, or categorical and continuous attributes respectively, we attain the naive bayesian classifier without preamble

    本文針對離散值屬性情形和連續值屬性情形分別構造了保持隱私的后驗概率計算協議，最後獲得安全的樸素貝葉斯分類器協議。
  11. Specifically, aiming at two widely used algorithms in data mining, naive bayesian classifier and boolean association apriori algorithm. we have brought forward two corresponding protocols incorporating privacy concerns. we have used secure multi - party computation protocols and tools to get the solutions

    本文針對數據挖掘中應用較為廣泛的樸素貝葉斯分類器和關聯規則的apriori演算法，利用安全多方計算的理論和工具，給出了與其相應的隱私性演算法。
  12. Along the medial axes with the same steps, we can get the average integral gray profile and the width profile. 3. karyotype classification of chromosome : according to the chromosome ’ s geometrical parameters, the karyotype classification are realized through the normal bayes classifier or fuzzy clustering based on the character of average integral gray profile

    利用染色體的中線等步長提取平均積分輪廓和寬度輪廓; 3 、染色體的核型分類:利用染色體結構參數即其灰度輪廓通過正態貝葉斯分類器或採用模糊聚類的方法來實現染色體的對號分類。
  13. Classification has always been a central issue on data mining, machine learning and pattern recognition, classifier, as an important model and method of machine learning and data mining, is very important to the development and application of machine learning and the data mining. the classifier ’ s effect closely correlates with the characteristic of data sets, at present, the construction of classifier is generally based on the character of different datasets, there is no such a classifier which is suitable for any data sets. under uncertain conditions, the bayes network is a powerful tools for the knowledge expression and inference, but for difficulties in constructing its network structure and very high time complexity, it has not been considered as a classifier algorithm until the emergence of na ? ve - bayes classifier

    分類一直是數據挖掘、機器學習和模式識別等研究的核心問題，貝葉斯網路是作為知識表示和推理的強大工具，由於搜索空間巨大和學習困難的原因，直到樸素貝葉斯理論的出現才被作為分類器演算法，改進樸素貝葉斯分類器是貝葉斯分類器學習的一個主要的研究方向。遺傳演算法本質上是一種求解問題的高效并行全局搜索演算法，適合應用於那些改進的分類器的結構學習中。本文提出了一種基於遺傳演算法的ban分類器演算法。
  14. The thesis analyses and parses openoffice. org document from text classification viewpoint, depicts the methods of extracting content, formatting, structure and descriptive information, which are most related to classification, from openoffice. org documents, and then constructs three different classification models for openoffice. org documents, respectively called label components classifier, structure components classifier and comprehensive classifier. the thesis implements these three classifiers through na ? ve bayes

    本文從面向分類的角度深入地分析了openoffice . org文檔，描述了從文檔中抽取與分類最相關的內容和格式、結構以及文檔描述信息的方法，構建了標簽組件法、結構組件法和綜合法三種不同的文本分類模型，最後用樸素貝葉斯方法實現了openoffcice . org文檔的三種分類器。
  15. This paper presents a method of automatic text categorization for chinese web pages, which mainly includes such models as chinese web pages acquirement, chinese word splitter, feature selection and native bayes machine learning and classification

    摘要提出了一種中文網頁自動分類的方法，主要包括中文網頁的自動抓取、中文分詞、特徵選取、貝葉斯機器學習與分類等功能模塊。
  16. A selective tree - augmented bayesian network classifier based on rough set theory

    一種基於粗糙集合理論的樹擴張型貝葉斯網路分類器
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