貝葉斯的 的英文怎麼說

中文拼音 [bèiyèsīde]
貝葉斯的 英文
bayesian
  • 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
  • 的 : 4次方是 The fourth power of 2 is direction
  • 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. 3 ) we try to import the bayesian adaptation, which is widely used in speech recognition, into speaker verification. we use bayesian maximum a posteriori estimation training a speaker model from background model, to solve the problem of model miss matching in speaker verification system

    3 ）為了解決說話人確認中存在的模型不匹配問題，嘗試將語音識別中的貝葉斯自適應演算法引入到基於高斯混合統一背景模型的說話人確認系統。
  2. The origin of the concept of obtaining posterior probabilities with limited information is attributable to thomas bayes.

    根據有限的信息得到的后定概率的概念最初是貝葉斯創造的。
  3. A doa estimation algorithm for multipath signals based on burg iterations

    基於貝葉斯網路的并行分佈估計演算法研究
  4. The paper analyzed safety level of certain road in tongzhou district of beijing by multivariate regression empirical bayes approach. result of the analysis effectively overcomes the chanciness of historical accident data

    本文利用多元回歸經驗貝葉斯法分析了北京市通州區某道路的安全水平，分析結果有效的克服了歷史事故數據的偶然性。
  5. Research for the classifiers based on bayesian networks

    基於貝葉斯網路的分類器研究
  6. Research on dynamic bayesian networks in non time homogenous markov decision process

    具有丟失數據的貝葉斯網路結構學習研究
  7. Spam filtering gateway based on nb algorithm

    基於樸素貝葉斯演算法的垃圾郵件網關
  8. In the model, one supposition is that the negotiant is risk neutral and rational. the other supposition is that the investors especially individual investors who acquire real information are irrational. we found irrational herding model of individual investors with the securities transaction mechanism and baye as well as the utility function of the information gainers

    在模型中假設做市商風險中性且理性、知情投資者尤其是個人知情投資者為非理性，通過證券交易機制和貝葉斯學習過程以及建立非理性知情投資者的效用函數來建立非理性影響下的個體投資者羊群效應模型，得到不同情緒狀態和對信息反應程度下個體投資者賣出羊群效應發生的條件。
  9. Elaborate process descriptions of evaluating offers, belief revision and proposing counteroffers are presented, in particular, we analyze the use of bayesian learning and reinforcement learning in negotiation process, restructuring the traditional q - learning into a dynamic q - leaming algorithm by introducing current beliefs and recency exploration bonus

    在該談判模型的基礎上引入學習機制，並分別對評估提議、更新信念、生成提議等談判過具有學習機制的電子商務自動談判研究摘要程作了詳細闡述，重點分析了貝葉斯學習和強化學習技術在自動談判中的應用。
  10. Video image segmentation based on bayesian learning

    基於貝葉斯學習的視頻圖像分割
  11. A document searching system with vector space model

    基於向量空間模型的貝葉斯文本分類方法
  12. An improved naive bayesian categorization algorithm for html

    文檔的樸素貝葉斯分類演算法
  13. The class of distributions includes the weibull, burr - type x, pareto and beta distributions. a proper general prior density function is suggested, and predictive density functions are obtained in one - and two - sample cases when the history sample is a type ii double censored sample. illustrative examples are given

    在type雙刪失數據場合下，討論了雙參數burr - type分佈參數的貝葉斯估計，在所取的損失函數分別為平方損失， linex損失，熵損失函數下得到了參數的貝葉斯估計，並且給出一種近似演算法。
  14. Compared with the regular rule - based expert system, the bayesian network based es can reason on the incomplete input information using the prior probability distribution ; the topological structure of the network being used to express the qualitative knowledge and the probability distributions of the nodes in the network being used to express the uncertainty of the knowledge, which made the knowledge representation more intuitively and more clearly ; applying the principle of the bayesian chaining rule, bidirectional inference which allow infer from the cause to the effect and from the effect to the cause can be achieved

    與一般基於規則的專家系統相比，貝葉斯網專家系統利用先驗概率分佈，可以使推理在輸入數據不完備的基礎上進行；以網路的拓撲結構表達定性知識，以網路節點的概率分佈表達知識的不確定性，從而使不確定性知識的表達直觀、明確；利用貝葉斯法則的基本原理，可以實現由因到果及由果到因的雙向推理。
  15. Cbr systems have lots of strongpoints, such as the completely expressing of the information, the incrementally learning, the precisely simulating of the visualized thought, the conveniency of the obtaining knowledge, the h igh efficiency of solving new things and so on

    Cbr的顯著優點有：信息的完全表達，增量式學習，形象思維的準確模擬，知識獲取較為容易，求解效率高等。本論文研究了貝葉斯網路、範例推理以及貝葉斯網路在範例推理中的應用。
  16. A high effective network intrusion detection system based on tree augmented na ve bayes

    基於樹擴展樸素貝葉斯的高效網路入侵檢測系統
  17. Prediction of seismic disasters based on fuzzy - bayes theory

    基於模糊貝葉斯的震害預測
  18. In the paper, the models of uncertain reasoning are focused, such as the reasoning model of bayes probability, reliability theory, d - s evidence theory and neural network

    本文主要涉及的不確定推理模型包括主觀貝葉斯的概率推理模型，可信度理論推理模型，證據理論及其改進推理模型以及神經網路推理模型。
  19. Data generalization is a kind of data model in knowledge mining. fuzzy entropy and fuzzy modifying bayesian method are used to generalize the trouble diagnosis data in fms

    採用基於模糊熵的最大增益和模糊修正貝葉斯的類屬演算法，計算fms的故障分類問題，說明了知識挖掘的數學過程。
  20. 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。
分享友人
分享到 Line

分享到臉書