risk minimization造句
例句與造句
- It can solve small - sample learning problems better by using experiential risk minimization in place of structural risk minimization
由于采用了使用結(jié)構(gòu)風(fēng)險最小化原則替代經(jīng)驗風(fēng)險最小化原則，使它較好的解決了小樣本學(xué)習(xí)的問題。 - Because of the lack of training samples , traditional methods based on experiential risk minimization can not play well in recognizing the characters
由于訓(xùn)練樣本不足,決定了采用傳統(tǒng)的基于經(jīng)驗風(fēng)險最小化原則的識別方法難以取得較好的識別效果。 - Because neural network is based upon empirical risk minimization and asymptotic theories , it is suitable to deal with situations where the amount of samples is tremendous and even infinite
神經(jīng)網(wǎng)絡(luò)的理論基礎(chǔ)是最小化經(jīng)驗誤差，這種基于傳統(tǒng)的漸進(jìn)理論的學(xué)習(xí)方法，在訓(xùn)練樣本點無窮多時是適用的。 - Structure risk minimization based weighted partial least - squared method weighted partial least - squared wpls method was proposed to achieve structure risk minimization in the partial least - squares modeling process
為了在偏最小二乘法pls建模過程中實現(xiàn)結(jié)構(gòu)風(fēng)險最小化srm ，提出基于結(jié)構(gòu)風(fēng)險最小化的加權(quán)偏最小二乘法wpls 。 - Aimed at the character of the agriculture system , the least squares support vector machine prediction model is given based on the principle of the statistical learning theory and structural risk minimization
針對農(nóng)業(yè)生產(chǎn)系統(tǒng)的特征，在統(tǒng)計學(xué)習(xí)理論和結(jié)構(gòu)風(fēng)險最小化原理的基礎(chǔ)上，建立了基于最小二乘支持向量機(jī)的時間預(yù)測模型。 - It's difficult to find risk minimization in a sentence. 用risk minimization造句挺難的
- 1 . a modified denoising method based on vc dimension and wavelet package is presented , improving the shortcomings of denoising methods based on empirical risk minimization and wavelets thresholds
針對傳統(tǒng)的基于經(jīng)驗風(fēng)險最小化信號消噪方法和現(xiàn)有的小波閾值信號消噪方法的不足，基于統(tǒng)計學(xué)習(xí)理論，提出了一種改進(jìn)的vc維小波包信號消噪方法。 - Based on analysis of the conclusions in the statistical learning theory , especially the structural risk minimization and the - insensitive loss function , a novel linear programming support vector regression is proposed
摘要通過對統(tǒng)計學(xué)習(xí)理論中的支持向量回歸問題，特別是結(jié)構(gòu)風(fēng)險問題和-不敏感函數(shù)的分析，得到了一種新的支持向量回歸算法。 - An novel support vector regression ( svr ) algorithm based on structural risk minimization inductive principle instead of empirical risk minimization principle was firstly introduced in well logs intelligent analysis
摘要基于核學(xué)習(xí)的支持向量機(jī)，是一種采用結(jié)構(gòu)風(fēng)險最小化原則代替?zhèn)鹘y(tǒng)經(jīng)驗風(fēng)險最小化原則的新型統(tǒng)計學(xué)習(xí)方法，具有完備的理論基礎(chǔ)。 - Support vector machine ( svm ) is a new method for pattern recognition based on the statistical learning theory . it is an implementation of structure risk minimization principle in the statistical learning theory
支持向量機(jī)( svm )是在統(tǒng)計學(xué)習(xí)理論基礎(chǔ)上發(fā)展起來的一種新的模式識別方法，它是統(tǒng)計學(xué)習(xí)理論中的結(jié)構(gòu)風(fēng)險最小化思想在實際中的一種體現(xiàn)。 - Support vector machines ( svm ) are a kind of novel machine learning methods . it can solve small - sample learning problems better by using experiential risk minimization in place of structural risk minimination
支持向量機(jī)( supportvectormachines ，簡稱svm )是在統(tǒng)計學(xué)習(xí)理論的基礎(chǔ)上發(fā)展起來的一種新的學(xué)習(xí)方法，它已初步表現(xiàn)出很多優(yōu)于已有方法的性能。 - Statistical learning theory focuses on the rule of machine learning with small sample sets . support vector machine is a new generated machine learning technique based on vc dimension and structural risk minimization
統(tǒng)計學(xué)習(xí)理論是一種專門研究小樣本情況下機(jī)器學(xué)習(xí)規(guī)律的理論,在統(tǒng)計學(xué)習(xí)的vc維理論和結(jié)構(gòu)風(fēng)險最小化原理的基礎(chǔ)上,發(fā)展了支持向量機(jī)理論。 - A modified svm model , which can predict peak recognition theory , was proposed in this paper . this model can increase the weight of peak error in the loss function of structural risk minimization , thus improve prediction accuracy of hourly water demand peak
本文提出一種能夠進(jìn)行峰值識別的改進(jìn)svm算法，該算法在結(jié)構(gòu)風(fēng)險最小化準(zhǔn)則的目標(biāo)函數(shù)中加大峰值誤差的權(quán)重，從而提高時用水負(fù)荷峰值的預(yù)測精度。 - In this paper , a new method of signal de - noising is presented with three important factors being taken into consideration , that are mother functions , function order and the number of functions , and the proposed method is based on structural risk minimization ( srm ) and wavelet threshold method
摘要基于結(jié)構(gòu)風(fēng)險最小化方法將改進(jìn)的小波變換用于故障信號消噪，它考慮的三個重要因素是：基函數(shù)，基函數(shù)排序和基函數(shù)個數(shù)選取。 - On the one hand , based on structure risk minimization least squares support vector machine algorithm can gain best results with existing information . the condition of infinite stylebooks is unnecessary . so the outcome is good based on this algorithm when the stylebooks are few
仿真研究了最小二乘支持向量機(jī)分類器在不同觀測數(shù)據(jù)長度時、采用不同核函數(shù)和不同分類方法時的性能,得出最小二乘支持向量機(jī)分類器對不同的模型具有一定不敏感性的結(jié)論。 - Statistical learning theory ( slt ) is based on the structural risk minimization ( srm ) principle , and it is a new set of theory system , which specially aims at machine learning issues under the circumstances of small - sample . based on this slt , supporting vector machine ( svm ) method has been developed as a new machine learning algorithm and also practical applications of slt
統(tǒng)計學(xué)習(xí)理論建立在結(jié)構(gòu)風(fēng)險最小化原則基礎(chǔ)上,它是專門針對少樣本情況下機(jī)器學(xué)習(xí)問題而建立的一套新的理論體系,支持向量機(jī)就是在統(tǒng)計學(xué)習(xí)理論這一基礎(chǔ)上發(fā)展起來的一種新的機(jī)器學(xué)習(xí)算法,它是統(tǒng)計學(xué)習(xí)理論的具體應(yīng)用。
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