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regression estimation in Chinese

Pronunciation:
How to pronounce "regression estimation""regression estimation" in a sentence

Translationmobile phoneMobile

  • 回歸估計(jì)
  • 通過測(cè)量風(fēng)洞壁壓力來(lái)估算升力

Examples

  • Fuzzy svms for regression estimation are developed in chapter 2
    針對(duì)回歸估計(jì)問題提出了模糊svm 。
  • A regressive prediction model containing recursive kernel regression estimation
    一種包含遞歸的核回歸估計(jì)的回歸預(yù)測(cè)模型
  • ( 3 ) the performance of support vector machine ( svm ) for regression estimation was studied
    ( 3 )支持向量機(jī)( svm )的參數(shù)對(duì)其回歸估計(jì)性能有很大影響。
  • In this class we describe support vector machines for regression estimation and illustrate the connection between svms and basis pursuit de - noising
    課中將敘述支持向量機(jī)的回歸估算法并舉例說(shuō)明支持向量機(jī)和基礎(chǔ)追蹤去雜訊法之間的關(guān)系。
  • For the regression estimation when the auxiliary variate is correlated with the disturbance , the bias and mean square error ( mse ) of the regression estimator are obtained , and the estimator of the mse is presented
    摘要討論了輔助變量與擾動(dòng)項(xiàng)相關(guān)條件下的回歸估計(jì)，給出了在這種條件下回歸估計(jì)量的偏差和均方誤差以及均方誤差的估計(jì)。
  • By applying generalized svm and least square svm of classification to regression estimation problem , fuzzy generalized weighted svm and fuzzy multiplayer least square generalized svm are proposed . 3
    把針對(duì)分類問題的廣義svm及最小二乘廣義svm用來(lái)處理回歸估計(jì)問題，并和模糊svm結(jié)合起來(lái)形成了基于模糊加權(quán)的廣義svm和基于模糊的多層最小二乘廣義svm 。
  • Svm , developed from that theoretical architecture , is a highly adaptive method , which is applied in the areas of pattern recognition , regression estimation , function approximation and density estimation
    在這一理論基礎(chǔ)上發(fā)展了一種新的通用學(xué)習(xí)方法一支撐向量機(jī)svm 。它是一種普遍適用的方法，已經(jīng)廣泛的用于模式識(shí)別、回歸估計(jì)、函數(shù)逼近、密度估計(jì)等方面。
  • Fuzzy c - clustering svm and least square svm for multiclass regression estimations is presented in chapter 3 , this method can estimate multiple regressions while clustering the samples . multi - output svm and multi - output least square svm are discussed for multiclass regression estimations
    在討論多類回歸模型估浙江大學(xué)博士學(xué)位論文計(jì)問題的基礎(chǔ)上又針對(duì)多個(gè)輸出的問題討論了svm和ls一svm如何實(shí)現(xiàn)的問題。
  • In this paper , an integral scheme of 16 position error calibration and autonomous alignment for three axis platform is given . it may calibrate 33 errors in all . first , determine parameters with least square estimate , then bayes method , ridge regression estimation were discussed separately
    本文設(shè)計(jì)了一個(gè)十六位置誤差標(biāo)定方案,可以分離出總計(jì)33項(xiàng)誤差,首先用最小二乘估計(jì)方法進(jìn)行參數(shù)辨識(shí),而后,分別研究了基于bayes方法的誤差系數(shù)辨識(shí),基于嶺估計(jì)的誤差系數(shù)辨識(shí)。
  • Since the range estimation is very important in the power system , after monte - carlo simulation method for the ranks is presented in this paper , and using binomial regression estimation to finish the three parameters range estimation . finally , the flowchart and the example of application of the three parameters range estimation is accomplished
    由于區(qū)間估計(jì)在工程應(yīng)用中更具有實(shí)際意義，本文提出了采用monte - carlo模擬法估計(jì)出分位秩后，再進(jìn)行二項(xiàng)式回歸處理來(lái)實(shí)現(xiàn)三參數(shù)區(qū)間估計(jì)的新方法，并用此方法實(shí)現(xiàn)了三參數(shù)的區(qū)間估計(jì)，同時(shí)給出了三參數(shù)區(qū)間估計(jì)的程序框圖和應(yīng)用實(shí)例。
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