decision-tree classifier 中文意思是什麼

decision-tree classifier 解釋
樹形判定分類法
  • decision : n. 1. 決定。2. 判決。3. 決議。4. 決心；決斷。5. 【美拳】（根據分數而不是根據擊倒對方做出的）裁判。
  • tree : n 特里〈姓氏〉。n 1 樹〈主要指喬木，也可指較大的灌木〉。 ★玫瑰可以稱為 bush 也可以稱為 tree 2 木...
  • classifier : n. 1. 分類者。 2. 【礦物】分級機。3. 【化學】分粒器。4. （漢語等中的）量詞。
  1. On the basis of analyzing the classification principle of decision tree classifier and parallelpiped classifier, a new classification method based on normalized euclidian distance, called wmdc ( weighted minimum distance classifier ), was proposed

    通過分析多重限制分類器和決策樹分類器的分類原則，提出了基於標準化歐式距離的加權最小距離分類器。
  2. A decision tree classifier using a scalable id3 algorithm is developed by microsoft visual c + + 6. 0. some actual training set has been put to test the classifier and the experiment shows that the classifier can successfully build decision trees and has good scalability

    最後著重介紹了作者獨立完成的一個決策樹分類器。它使用的核心演算法為可伸縮的id3演算法，分類器使用microsoftvisualc + + 6 . 0開發。
  3. It is demonstrated by simulation data. as for classifier, it presents the artificial neural network. based on three methods of modulation recognition and decision tree classifier and neural network classifier, experimentations have been carried through

    在分類器設計方面，介紹了利用神經網路進行模式識別的原理，採用前述的三種特徵提取方法，分別結合判決樹分類器和神經網路分類器對信號進行分類，並且進行了試驗論證。
  4. 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。
  5. Data warehouse is a hot research area in 90s its main motif is to provide the decision - maker a powerful tool : gathering the data in pure consistent, relevant pattern, and making use of the data in managing analyzing, data - mining purposec that means that the decision - maker can use the tool to understand, grasp the situation of the business from different directions and forecast the future of it when using data warehouse, the processing speed determines data warehouse ' s practicability and processing ability the hoc ( highway decision center ) system realized before solves some key problems about intermediate scale data, mainly concentrating data warehouse performance coefficient when using hdc in large scale data, it encountered processing speed problem then the settlement of this problem becomes a major research point so, based on the former research achievements, the present task is to construct the renowned data warehouse architecture and its relevant algorithms, then adapts the system to the large scale dataset with data mining functions c this paper is a part of the research in order to construct the powerful system, a key problem is to cope with the processing - speed problem and the data space problem, etc, - caused by the large scale dataset and magnificent dataset this is also the core in the present data mining research this paper ' s motive is to design and realize a decision - tree classifier in the data warehouse system for large - scale dataset

    大型數據倉庫的處理速度問題目前是制約其推廣應用的關鍵所在，也是這一領域的一個重要研究課題，也正是我們當前工作的重點：在前期研究工作的基礎上圍繞提高大型數據倉庫處理速度問題，建立改進的數據倉庫系統模型和相關演算法，開發出面向中級以上企事業單位的、具有數據挖掘和分析能力的大型數據倉庫系統。建立大型數據倉庫所面臨的關鍵問題，是如何妥善解決實際業務數據的大規模、海量特徵所帶來的處理速度和空間等問題，這也是當前挖掘技術研究必然面對的核心問題。本研究的目的是設計並實現大型數據倉庫系統中的分類數據挖掘工具? ?決策樹分類器，主要工作是在綜合了解現有決策樹分類演算法的研究情況的前提下，對決策樹演算法適應大規模數據集的問題進行探討，力求設計出能較好地適應大規模數據的分類器演算法。
  6. 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。
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