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regression tree in Chinese

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

Translationmobile phoneMobile

  • 退化樹

Examples

  • Bayesian - network based regression tree learning algorithm
    基于貝葉斯網(wǎng)絡(luò)的回歸樹學(xué)習(xí)算法
  • Secret is a new algorithm for scalable linear regression trees
    Secret是一個(gè)關(guān)于可伸縮線形回歸樹的算法。
  • Improves on the classification and regression trees technology , increases it ' s classification precision
    對(duì)分類回歸樹數(shù)據(jù)挖掘技術(shù)進(jìn)行了改進(jìn),使之具有更高的分類精度。
  • The thesis combines generalized computing theory with classification and regression trees technology , makes the great theory innovation
    本文把廣義計(jì)算理論和數(shù)據(jù)挖掘技術(shù)相結(jié)合,具有很強(qiáng)的理論創(chuàng)新意義。
  • Combines multi - rules neural network with classification and regression trees technology based on generalized computing theory , implements the abnormal customers recognition system
    基于廣義計(jì)算思想,把多準(zhǔn)則神經(jīng)網(wǎng)絡(luò)和分類回歸樹技術(shù)相結(jié)合,實(shí)現(xiàn)異動(dòng)客浙江大學(xué)碩士學(xué)位淪義綴戶識(shí)別系統(tǒng)。
  • The first part of this thesis describes the theory of rbf neural networks . the input space is thus divided into hyperrectangles organized into a regression tree ( binary tree ) by recursively partition the input space in two
    第一部分從rbf網(wǎng)絡(luò)出發(fā),通過遞歸分割將輸入空間劃分為兩部分,從而將輸入空間變成一個(gè)用超矩形構(gòu)成的回歸樹(二叉樹) 。
  • Based on the generalized computing theory , the thesis combines multi - rules neural network with a kind of decision tree - classification and regression trees . further more , we put forward a new kind of abnormal customers recognition model
    為進(jìn)行客戶關(guān)系管理,本文基于廣義計(jì)算思想,將多準(zhǔn)則神經(jīng)網(wǎng)絡(luò)和一種決策樹? ?分類回歸樹相結(jié)合,提出了一種新的異動(dòng)客戶識(shí)別模型。
  • Chapter three is about credit risk measurement methodology such as zeta model , credit scoring - model , classification & regression tree , csfp model and credit metrics , the latest of which can measure the credit risk of abs / mbs dynamically
    包括zeta法、資信評(píng)估模型、分類和回歸樹、 cspp開發(fā)的信用風(fēng)險(xiǎn)附加模型;動(dòng)態(tài)評(píng)估資產(chǎn)證券化的信用風(fēng)險(xiǎn)技術(shù)? ?信用風(fēng)險(xiǎn)計(jì)量法。
  • You can use multiple algorithms within one solution to perform separate tasks , for example by using a regression tree algorithm to obtain financial forecasting information , and a rule - based algorithm to perform a market basket analysis
    可以在一個(gè)解決方案中使用多個(gè)算法來執(zhí)行不同的任務(wù),例如,使用回歸樹算法來獲取財(cái)務(wù)預(yù)測信息,使用基于規(guī)則的算法來執(zhí)行市場籃分析。
  • The model can improve classification precision and recognition efficiency effectively , make full use of the advantages of multi - rules neural network and classification and regression trees , and make up their respective disadvantages at a certain extent
    該模型能夠有效提高分類精度和識(shí)別效率,充分利用多準(zhǔn)則神經(jīng)網(wǎng)絡(luò)和分類回歸樹各自的優(yōu)點(diǎn),一定程度上避免各自的缺陷。
  • More examples:  1  2
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