decision trees 中文意思是什麼

decision trees 解釋
決策樹方法
  • 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。
  • trees : 目錄樹
  1. Decision trees are widely applied in data mining for its character such as simplicity and concision compared with other classification models

    在數據挖掘領域，相對于其它而言模型決策樹具有簡潔、高效等特點，故其應用最為普遍。
  2. Application of covariance and correlativity coefficient to the designing of decision trees

    協方差及相關系數在決策樹構造中的應用
  3. Decision trees have standard symbols: squares symbolize decision points, and circles represent chance events.

    決策權樹有統一的符號：方框表示決策點，圓圈表示可能的事件。
  4. One of the best ways to analyze a decision is to use so-called decision trees.

    所謂決策樹是進行決策分析的最佳方法之一。
  5. Microsoft decision trees algorithm enhancements

    Microsoft決策樹演算法方面的增強功能
  6. Exploring decision trees as a tool to investigate money laundering

    決策樹演算法在反洗錢領域中的應用研究
  7. Microsoft decision trees algorithm

    Microsoft決策樹演算法
  8. All of theses database was integrated into a land information system, which can be used to land evaluation and land use analysis. the second part is the application of soter land information system in land evaluation, based on water balance model watsat, crop simulation model ps 123 and ales ( automated land evaluation system ). the handan land evaluation model was built in ales based on expert knowledge and farmer s " experiences, it includs three decision trees, namely soil erosion risk, soil water condition and soil fertility

    以邯鄲地區1 25萬soter土壤土地數據庫為基礎，探討了土壤參數區域化問題，並利用watsat區域水分平衡模型，研究了邯鄲地區區域水分平衡：大部分地區土壤水分滿足夏玉米生長需求， （ suff ）值為0 . 8 - 1 . 0 ，非常適宜；部分地區如大名地區、邯鄲和永年部分地區、涉縣溝谷坡梁地區土壤水分適宜夏玉米生長， suff值0 . 4 ? 0 . 8 ；不適宜地區， suff值0 . 2 ? 0 . 4 ，主要集中於丘陵山區以及平原古河谷地礫石和粗砂分佈區。
  9. 2. investigating how to model the wsd. the na ? ve bayes model, maximum entropy, support vector machine and decision trees model are examined in chinese wsd

    2 .考察了貝葉斯模型、最大熵模型、支持向量機和決策樹模型等四種數學建模方法在詞義消歧上的應用效果。
  10. In this paper, we begin with accuracy of decision trees. we redefine tree nodes of traditional tree and define the concept that is called majority leaf nodes. we call those class labels as majority class leaf nodes whose percentage of any class distribution is large than the assumed threshold value

    即當一個葉子節點的類別分佈中某一個類別分佈大於指定的閾值時（如0 . 51 ） ，我們就把這個類別稱為大多數類，相應的葉子節點就稱為大多數類葉子節點，其它的類別稱為少數類。
  11. On the other hand, dm can exploration and uncover meaningful patterns and rules from data with some mining algorithms such as clustering, decision trees, association rules and so on

    數據挖掘技術則通過聚類、決策樹和關聯規則等挖掘演算法從數據的海洋中探索和發現有用的信息和知識。
  12. Credit assessment is a very important but rather complicated process for commercial banks. from the past decades to nowadays, different schemes using simple financial ratios and many other statistical methods, such as logistical regression analysis, linear regression analysis, decision trees and so on, are used popularly by commercial banks all of the world

    在國內，銀行對客戶的信用等級評定，還處在對企業的某些財務指標進行評價，而後加權平均確定的階段上，因此迫切需要引入更為科學的方法來確定有效指標，並建立準確的定量模型來解決信用評估問題。
  13. Therefore, individual-preference curves should be substituted for statistical probabilities in decision trees.

    因此，在決策樹中個人的偏好曲線應當取代統計機率。
  14. Cases are triggered by the index which is gotten from knowledge represented by decision trees and diagnostic conclusions derived from the two approaches are output by synthesize

    用決策樹知識作為有關案例知識的索引對案例進行觸發，對二者得到的診斷結論進行綜合后輸出。
  15. Solving multiple - instance and multiple - part learning problems with decision trees and decision rules. application to the mutagenesis problem. lecture notes in artificial intelligence 2056, stroulia e, matwin s eds.,

    由於本文已經揭示出多示例學習與監督學習之間具有密切聯系，因此本文提出通過建立多示例集成來求解多示例學習問題。
  16. Decision trees algorithm

    決策樹演算法
  17. This viewer displays mining models that are built with the microsoft decision trees algorithm

    該查看器顯示使用microsoft決策樹演算法生成的挖掘模型。
  18. Some classical clustering algorithms and decision trees algorithms are analyzed and compared

    並具體分析比較了多種的典型聚類和決策樹數據挖掘演算法。
  19. Integrated inference mechanism based on decision trees and cases is implemented

    實現了基於決策樹和案例的集成推理機制。
  20. 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。
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