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bayes
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  贝叶斯
     Application of Bayes Discriminant Analysis in Safety Evaluation
     贝叶斯(Bayes)判别分析理论在安全评价中的应用
短句来源
     The Gamma distribution function Γ(x|α,β),α>0,β>0 is always used as a prior distribution density function of bayes expontional reliability growth model.
     Gamma分布函数Γ(x|α,β),α>0,β>0通常用做贝叶斯指数可靠性增长模型的先验分布密度函数。
短句来源
     Study of the Application of Bayes Thorey and Methods in Identifying Syndrome in TCM
     贝叶斯原理与方法及其在中医证候识别中的应用研究
短句来源
     Results Experiments on 200 ultrasonic images, randomly divided into training set 100 and prediction set 100, showed that the Accuracy of SVM, Bayes, BP and Fisher was 0.960, 0.940, 0.932±0.013, 0.930 respectively.
     结果基于200例病例随机划分为训练集100例和测试集100例进行测试,支撑矢量机、贝叶斯分类器、BP网络和Fisher线性判别器的Accuracy分别为0.960,0.940,0.932±0.013,0.930。
短句来源
     Weighted Naive Bayes Classification Algorithm Based on Rough Set
     基于Rough Set的加权朴素贝叶斯分类算法
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  贝斯
     Manchu Character Recognition Post-Processing Based on Bayes Rules and Substitution Set Confusion Matrix
     基于贝斯准则和待定词集模糊矩阵的满文识别后处理
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  “bayes”译为未确定词的双语例句
     Empirical Bayes Estimation with Convergence Rates about a Class of Discrete Distribution Families
     一类离散分布参数的经验Bayes估计的收敛速度
短句来源
     Some Notes on Johns' Empirical Bayes Estimation
     关于Johns的经验Bayes估计的几点注记
短句来源
     ASYMPTOTICALLY OPTIMAL EMPIRICAL BAYES ESTIMATORS OF CONTINUOUS FUNCTIONS OF THE PARAMETER IN ONE DIMENSIONAL DISCRETE EXPONENTIAL FAMILY
     一维离散指数族参数的连续函数的渐近最优经验Bayes估计
短句来源
     Empirical Bayes Estimates for Binomial Parameters I——the Case of Loss Function(p-d)~2
     二项分布参数的经验Bayes估计Ⅰ—损失函数为(p-d)~2的情况
短句来源
     The Asymptotically Optimal(a,o)Empirical Bayes(EB)Estimation about a Class of Discrete Distribution Families
     一类离散分布参数的渐近最优经验Bayes估计
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  bayes
We present a new scheme for uncertain reasoning based on Bayes' formula in likelihood ratio form in this paper.
      
The asymptotically optimal empirical bayes estimation in multiple linear regression model
      
Empirical Bayes estimation of the parameter vector θ=(β',σ2)' in a multiple linear regression modelY=Xβ+ε is considered, where β is the vector of regression coefficient, ε∽N(0,σI with σ2 unknown.
      
In this article, Bayes estimation of location parameters under restriction is brought forth.
      
Thus the results under Type- II right censoring can be used directly to get more accurate estimators by Bayes method.
      
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In this papér, it is discussed from the statistical points of view the two main topics related to classifying the grades of thickness irregularity of cotton yarn, namely: (1) the method for setting the grades intervals, and (2) the method for classifying the sampled population into one of the grades previously defined. Concept on the critical values for setting grade intervals is introduced and discussed, the errors in classifying the sampled population due to thsee values are also intesvigated. An example for...

In this papér, it is discussed from the statistical points of view the two main topics related to classifying the grades of thickness irregularity of cotton yarn, namely: (1) the method for setting the grades intervals, and (2) the method for classifying the sampled population into one of the grades previously defined. Concept on the critical values for setting grade intervals is introduced and discussed, the errors in classifying the sampled population due to thsee values are also intesvigated. An example for determining these values is given. The problem on sampling by variable or by attributer is discussed. In the problem of sampling by variables, the Neyman and Pearson's theory on two types of errors, as well as the concepts of indifferent intervals are employed in determining the sample size for the purpose of classification. The functional relation n~kσ~2 is suggested showing that the required sample size is proportional to the population variance of the irregularity index, while the constant is changed with respect to the size of indifferent intervals and values of α and β In the problem of sampling by attributes, the Bayes' theorem is employed to verify the reliability of information by the sample size of nine used in factories. It is shown that this sample size is statistically insufficient on some account. Some further problem have been pointed for the further investigation.

全文包括兩个主要部分:定級的数理统計原理和評級的数理統計原理。在定級方面,提出并討論了划分品級界限的临界值的概念和意义,还举了实例,以說明求得划分品级界限的临界值的方法。此外,还提出了获得标准样照的原則。在評級方面,討論了按量抽样法和按質抽样法。应用了尼们和彼亞蓀的二类誤差的理論,而求得样本大小n与总体不勻率均方差σ的关系,进而以实例說明n=9的样本个体数太小的事实。作者在討論中,建議將按質抽样檢驗方法轉化为抽量检验法以評定品級,并指出这样做法是可能而合理的。最后,提出了二項作进一步研究的方向。

The author first discussed the evaluation of the conditional probability and the general probability, and then discussed the evaluation of the compound probability. The first part of this paper deals with the conditional probabilities of fog for the different wind directions and shows that it is better calculated by the equation:P(F\W_i)=P(W_iF)/P(W_i) (1) where F represents the fog frequency and W_i represents the frequency of the wind from the direction i(i=1, 2,…16). By practical calculations it shows that...

The author first discussed the evaluation of the conditional probability and the general probability, and then discussed the evaluation of the compound probability. The first part of this paper deals with the conditional probabilities of fog for the different wind directions and shows that it is better calculated by the equation:P(F\W_i)=P(W_iF)/P(W_i) (1) where F represents the fog frequency and W_i represents the frequency of the wind from the direction i(i=1, 2,…16). By practical calculations it shows that the method adopted by M. Wurtele (1944) was unnecessary.The conditional probabilities of rainfall for the different wind directions have been calculated also by the same method as stated above. Furthermore, the attempts have been made to calculate the general probability of rainfall by applying the theorem of total probability and to calculate the conditional probability of wind direction after the rainfall has been observed by applying Bayes' theorem.In the second part it has been shown that P(B)=P(B_0)+P(B_1)+…+P(B_n), (2) where B denotes the event of having rain days at the station B; B_0 denotes the event of having rain days only at the station B; B_1 denotes the event that two stations including station B have rain days; B_2 denotes the event that three stations including the station B have rain days; and so on. Besides, by the theorem of compound probability the following formulas can be established: where i=1, 2,…n; i, j are taken for all combinations in the numbers 1, 2,…n; k=1, 2,…n except the numbers i and j; A_0=1.By formula (3) the probabilities of simultaneous occurrence of rain days at Hankow, Siangyang, Changsha and Chungking have been calculated for the different months. For the purpose of check the following three formulas have been derived in addition to the formula (2):P(B)=P(B_0)+2/3 P(B_1)+1/3 P(B_2)+1/3 [P(BA_1)+P(BA_2)+P(BA_3)], (4)P(BA_1)+P(BA_2)+P(BA_3)=P(B_1)+3/2 P(B_2)+3/2 P(B_3)+1/2 [P(BA_1A_2)++P(BA_2A_3)+P(BA_1A_3)] (5)andP(BA_1A_2)+P(BA_2A_3)+P(BA_1A_2)=P(B_2)+3P(B_3). (6)At last the author has demonstrated that the computation of the compound probability by formula (3) is more significant than that by direct computation from the definition of probability.

作者在本文中討論条件概率、一般概率与复合概率的計算方法,并且指出M.Wurtele計算各种风向时候雾的概率,所用的方法是不必要的。作者也計算了各种风向时的降水概率,并且根据总概率定理計算降水的一般概率,根据Bayes定理計算在降水出現的条件下风的概率. 其次,作者推导計算各台站同时为雨日的概率,并且推导校对公式,以便检查計算結果。

Based on our ten years' experience in diagnosis and differential diagnosis of primary liver cancer (PLC), positivities of 18 parameters including history, symptoms, signs, alpha fetoprotein (AFP) level, laboratory findings, ultrasound, liversoan, etc. have been selected for differential diagnosis of the following diseases; namely subclini-cal PLC, clinical PLC, AFP negative PLC or secondary liver cancer, liver cirrhosis in active stage, liver cirrhosis with atrophy, chronic hepatitis in active stage, liver hemangioma,...

Based on our ten years' experience in diagnosis and differential diagnosis of primary liver cancer (PLC), positivities of 18 parameters including history, symptoms, signs, alpha fetoprotein (AFP) level, laboratory findings, ultrasound, liversoan, etc. have been selected for differential diagnosis of the following diseases; namely subclini-cal PLC, clinical PLC, AFP negative PLC or secondary liver cancer, liver cirrhosis in active stage, liver cirrhosis with atrophy, chronic hepatitis in active stage, liver hemangioma, hepatic cyst and liver abscess. The probability of the diagnosis was calculated using Bayes Theory and employing APPLESOFT BASIC as programming language.237 pathologically verified oases covering all of the diseases mentioned above had been testified by a 48K APPLE TYPE II microcomputer. The total accuracy of computer-aided diagnosis of 237 oases of 9 types of disorders was 91.6% as compared with pathological diagnosis. Among them 155 cases of AFP positive PLC gained the highest accuracy 99.4%, while AFP negative PLC 89.2%. The overall accuracy rata in different disorders was: liver cancer 97.4% (187/192), hepatic cyst 85.7% (12/ 14), liver hemangioma 75.0% (9/12) and liver abscess 60% (3/5). It was rather difficult to differentiate cirrhosis and chronic hepatitis from liver cancer that the accuracy was reduced to 43% (6/14) only, according to the false negative (2.6%) and false positive (4.6%) were insignificant. The overall accuracy of computer-aided diagnosis might be comparable with clinical diagnostic accuracy by high level specialists of liver caneer (90.7%). It seems that computer-aided certainly has the definite advanges in differential diagnosis, confirming the diagnosis and suggesting the proper treatment during the early stage of liver cancer.

电子计算机在医学上的应用已有二十年历史,国内也有所开展。目前电子计算机分为微型(Micro)、小型(mini)、中型(Midi)、大型(maxi)和超级机(Supercomputer)。近年微型机发展极快,其内存容量已超过二十年前最大的计算机,其速度快、体积小,价格便宜。国外很多医院部门、实验室,甚至诊所都已广泛应用。本文报告肝癌的电子计算机鉴别诊断及237例验证的结果。

 
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