tree pruning 中文意思是什麼
tree pruning
解釋
樹狀修剪-
In this paper, the techniques for perennial dongzao tree of not bearing fruits are introduced, such as fertilizer and water management, the technical methods of increasing fruit - bearing rate, winter pruning, and disease and pests control and so on
本文主要介紹多年不結果冬棗樹的肥水管理、提高坐果率的技術措施、冬季修剪及病蟲害防治技術。 -
Summer pruning devitalises the tree on an extent and consequently reduces excessive vigour.
夏剪能在一定程度上減弱植株的生命力，從而削弱過分的生長勢。 -
Pruning and training are cultural practices which alter the natural development of the tree.
修剪和整形是改變植株自然生長的技術措施。 -
The discussion of tree training and pruning is still more or less slanted toward the large trees.
所論述的整形和修剪，或多或少仍傾向于大冠樹。 -
In order to identify the dependent relationship between words based on statistics efficiently and accurately, this paper has rectified part of the shortcomings of present algorithms by making the best of the distribution characteristic between words, distinguishing the collocation, coordinate and affiliation relationship between words, identifying them respectively by different strategies, presenting a new module of matching between strings and a new module of dependent intensity between words, constructing the tree of dependent relationship, pruning the constructed tree of dependent relationship and identifying some latent dependent relationship
摘要本文擴展和改進了現有的詞語間依存關系定量識別演算法，充分考慮詞項概率分佈的影響；明確區分詞項之間的搭配關系、並列關系和從屬關系，針對它們不同的特點，提出不同的識別演算法；提出字串匹配模型；充分考慮兩個詞項之間相互位置的離散分佈和距離的影響、以及它們的概率分佈特性，提出詞項間的依存強度模型，並據此構建詞語間依存關系樹；提出更新策略，對已經建好的依存關系樹進行裁剪，並挖掘出潛在的依存關系。 -
In the data mining prototype system, apriori algorithm of association rules mining, id3 algorithm of decision tree classification, c4. 5 pessimism estimate algorithm of decision tree classification and c4. 5 reduced - error pruning algorithm of decision tree classification are realized
在數據挖掘原型系統中，實現了關聯分析的apriori演算法、分類的id3決策樹演算法、 c4 . 5的悲觀估計決策樹演算法和c4 . 5決策樹的消除誤差修剪演算法（ reduced - errorpruning ） 。 -
Tree pruning can descend the existent noise of training set
剪枝的目的是降低由於訓練集存在噪聲而產生的起伏。 -
Based on the analysis of above drawbacks, this paper proposes frequent access pattern tree algorithm ( fapt ). this algorithm includes two steps : access pattern tree method, through the pattern matching method it saves user ' s visit sequences with tree ; pruning method, it uses frequent degree to prune access pattern tree which is under the frequent degree
在分析以上不足的基礎上，提出了頻繁訪問模式樹（ fapt ）演算法，該演算法包括以下兩個步驟:訪問模式樹的生成，通過模式匹配的方法將用戶訪問序列以樹形結構來存儲;修剪的策略，利用頻繁度對訪問模式樹進行修剪，修剪掉其中低於頻繁度的節點。 -
Heavy pruning was practiced to build up the strong tree framework required to bear the fruit in later years.
為了建成今後幾年內結果所要求的牢固骨架，需要採取重剪。 -
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演算法、最小代價?復雜性剪枝演算法以及最優樹選擇等演算法。提出了系統設計之後，論文詳細介紹了該系統的開發，用以解決異動客戶的識別問題。 -
( 2 ) the reasonable describing about dynamic fuzzy decision tree from attributes treatment to building the tree and then pruning tree, and it provides a certain extent stated theory foundation for ulteriorly researching dynamic fuzzy decision tree and establishes a main concept frame of dynamic fuzzy decision tree
（ 2 ）對動態模糊決策樹從屬性處理到構建以及剪枝給出了合理的描述，形成了動態模糊決策樹的基本概念框架。 -
Firstly, some basic algorithms for inducing decision tree are discussed, including id3, which uses information gain to select a splitting attribute when partitioning a training set ; c4. 5, which can deal with numeric attributes ; cart, which uses gini rule in attribute selection and induces a binary tree ; public, which puts tree pruning in the tree building phase ; interactive method, which puts artificial intelligence and human - computer interaction into the procedure of decision tree induction ; as well as sliq and sprint which are scalable and can be easily parallelized. advantages and disadvantages of these algorithms are also presented
文中詳細闡述了幾種極具代表性的決策樹演算法：包括使用信息熵原理分割樣本集的id3演算法；可以處理連續屬性和屬性值空缺樣本的c4 . 5演算法；依據gini系數尋找最佳分割並生成二叉決策樹的cart演算法；將樹剪枝融入到建樹過程中的public演算法；在決策樹生成過程中加入人工智慧和人為干預的基於人機交互的決策樹生成方法；以及突破主存容量限制，具有良好的伸縮性和并行性的sliq和sprint演算法。 -
The pruning of segmental roots and branches and the repair rectification of trees should be undertaken by qualified tree specialists
由合資格的樹木專家修剪樹根及樹枝和執行修補矯正樹木的工作。 -
This paper first illustrated some typical algorithms for large dataset, then gave off a processing diagram in common use second, for the dataset with large quantity and many attributes, we renovated the calculation method of the attribute ' s statistic information, giving off a ameliorated algorithm this thesis consists of five sections chapter one depicts the background knowledge and illustrates the position of data mining among many concepts also here is the data mining ' s category chapter two describes the thought of classification data mining technique, puts forward the construction and pruning algorithms of decision tree classifier chapter three discusses the problems of adapting data mining technique with large scale dataset, and demonstrates some feasible process stepso also here we touches upon the combination r - dbms data warehouse chapter four is the design of the program and some result chapter five gives the annotation the conclusion, and the arrangement of future research
本論文的組織結構為：第一章為引言，作背景知識介紹，摘要闡述了數據挖掘在企業知識管理、泱策支持中的定位，以及數據挖掘的結構、分類；第二章講述了分類數據挖掘的思路，重點講解了泱策樹分類器的構建、修剪，第三章針對大規模數據對數據挖掘技術的影響做了講解，提出了可採取的相應的處理手段，以及與關系數據庫、數據倉庫結合的問題；第四章給出了論文程序的框架、流程設計，以及幾個關鍵問題的設計；第五章對提出的設計進行簡要的評述，做論文總結，並對進一步的研究進行了規劃。 -
We also place emphasis on research of apriori and fp - growth algorithm and compare the performance of two algorithms. secondly, we do research on concepts of structured and nonstructured data, actual state and problems of tree structure mining, and freetreeminer algorithm theory. we also study canonical form and pre - processing technologies of free - tree, concepts and properties of closed and maximal tree, and pruning, growing and mining of tree structure
其次，研究了結構化與非結構化數據的基本概念、樹結構挖掘的研究現狀、現有樹結構挖掘技術存在的問題、 freetreeminer演算法及其基本思想，重點研究了free樹的規范化和預處理技術、封閉頻繁子樹和最大頻繁子樹的概念和性質、樹結構的剪枝和生長技術、樹結構的挖掘技術。 -
My research subject is based on the data warehouse called hdc ( highway decision center ) which our research group have finished previously. after i study the decision tree thoroughly, ! make some improvement on the problems existed in the model and the algorithm. and i finish the development of the classifier successfully. in order to improve the execution efficiency of the decision tree, this paper realizes the integration of the building phase and the pruning phase
本課題是在課題組前期完成的hdc （ highwaydecisioncenter ）數據倉庫平臺的基礎上進行的，在對cart決策樹進行了深入研究分析的基礎上，針對存在的問題對數學模型、演算法等進行了若干改進，最終獨立開發了基於數據倉庫平臺的適合大數據量cart分類器。 -
This paper organizes as follows : chapter 1 mainly introduces the research background, and gives a description of the research content of this paper after discusses the research trend on classification in dataming ; chapter 2 focuses on the theory of cart and gives a algorithm which integrates the tree building phase and pruning phase ; chapter 3 gives a detailed description on rbf and proposes the center selection method based on the statistic information of the training dataset. chapter 4 is the design and realization of the classifier. and chapter 5 summarize the work we i done and analyses the work to do later and obtain the research subject in the future
本論文的組織結構為：第一章為緒論，介紹了研究背景和分類分析研究領域國內外的研究動態，闡述了本文的主要研究內容；第二章詳細敘述了cart分類器的原理，給出了建樹與修剪階段合併的演算法；第三章描述了rbf神經網路分類器，給出了基於樣本統計的網路中心選取方法；第四章講述了cart分類器的設計與實現；第五章對本課題的研究工作進行了總結，分析了今後所要進行的工作以及進一步研究的課題。 -
These algorithms search the p / s ( publication / subscription ) tree using a heuristic pruning method to discover object instances with high efficiency, and generate the sending templates to facilitate the reflection of attributes updating
這些演算法使用啟發信息和剪枝條件搜索公布訂購樹，生成發送模板，提高了發現對象的搜索效率和數據更新時的反射發送效率。 -
Ansi z133. 1 - 1994 safety requirements for tree care operations - pruning, trimming, repairing, maintaining and removing trees, and cutting brush
樹木養護操作安全要求.修剪，削減，修整，保養和移動樹木及剪枝
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