- 分類和回歸樹
- classification: n. 1.選別；分等，分級(jí)；分選。 2.【動(dòng)、植】分類( ...
- regression: n. 1.復(fù)歸，回歸。 2.退步，退化。 3.【天文學(xué)】 ...
- tree: n. 1.樹〔主要指喬木，也可指較大的灌木〕。 ★玫瑰可 ...
- regression tree: 退化樹
- tree classification: 樹木分類
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classification and regression tree中文什么意思
- 分類和回歸樹
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- And then , the thesis brings forward a new modeling method - abnormal customers recognition system based on generalized computing and classification and regression trees . the system is composed of multi - rules neural network learning part and classification and regression trees processing part
然后，通過(guò)深入研究多準(zhǔn)則神經(jīng)網(wǎng)絡(luò)和決策樹的特點(diǎn)，論文提出了將多準(zhǔn)則神經(jīng)網(wǎng)絡(luò)應(yīng)用于決策樹的建模方法? ?基于多準(zhǔn)則神經(jīng)網(wǎng)絡(luò)和分類回歸樹的異動(dòng)客戶識(shí)別系統(tǒng)。 - The work that is carried out by me for this project as follows : at first , works over the decision tree technology and the multi - rules neural network theory based on the generalized computing , outlines the advantages and disadvantages of the two theories , analyzes the possibility to combine multi - rules neural network with classification and regression trees , and studies some achievement in this field
為完成這個(gè)項(xiàng)目，本人所做的工作具體如下：首先研究了數(shù)據(jù)挖掘技術(shù)中的決策樹技術(shù)和基于廣義計(jì)算的多準(zhǔn)則神經(jīng)網(wǎng)絡(luò)理論以及兩種理論的優(yōu)缺點(diǎn)。分析了多準(zhǔn)則神經(jīng)網(wǎng)絡(luò)和決策樹相結(jié)合的可能性及優(yōu)勢(shì)，并深入了解目前該方向的發(fā)展情況。 - Along with the rapid development of the technology of data warehouse and data mining , customer relationship management ( crm ) becomes more and more important . on this need , we advanced the project of abnormal customers recognition system based on generalized computing and classification and regression trees ( cart )
基于廣義計(jì)算和分類回歸樹異動(dòng)客戶識(shí)別系統(tǒng)這個(gè)項(xiàng)目，是在數(shù)據(jù)倉(cāng)庫(kù)技術(shù)和數(shù)據(jù)挖掘技術(shù)迅速發(fā)展的基礎(chǔ)上，針對(duì)企業(yè)客戶關(guān)系管理的迫切需要而提出的。 - Classification and regression trees processing part introduces growing algorithm of cart , pruning algorithm of cart and selecting best tree algorithm etc . on the basis of the concerned new model , the thesis presents in details the designing of multi - rules neural network based cart system for abnormal customers recognition
在分類回歸樹部分，介紹了分類回歸樹的生長(zhǎng)算法、最小代價(jià)?復(fù)雜性剪枝算法以及最優(yōu)樹選擇等算法。提出了系統(tǒng)設(shè)計(jì)之后，論文詳細(xì)介紹了該系統(tǒng)的開發(fā)，用以解決異動(dòng)客戶的識(shí)別問(wèn)題。
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