tree classification 中文意思是什麼

tree classification 解釋
樹木分類
  • 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...
  • classification : n 1 選別；分等，分級；分選。2 【動、植】分類（法）。 〈分類級別為： phylum 【動物；動物學】及 div...
  1. Study on classification of dust blocking effect of branches of landscaping tree species

    園林綠化樹種枝葉滯塵效果分類研究
  2. 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。
  3. Firstly the patterns of the multifingered hands are detailed, eight patterns are defined. the classical bayes method is used in the classification of pre - grasp of multiple fingers based on three patterns which are grasping, holding and pinching. based on the eight pre - grasp patterns, bp neural network is applied in the classification of the pre - grasp of multifingered hands and gets a good effect. the method solves the shortcoming input sample relying on the propobility density and simplified the un - insititution characters extraction. in this paper, support vector machine ( svm ) and binary - tree with clustering is applied in the classification. this method can solve the slow speed and effect with fewness sample in the classification, achieving a good effect. in this papper, we extract the characters of the regulation object with geometry characters and extact the unregulation object with the image analysis

    此法解決了輸入樣本依賴物體的概率密度的特點，簡化了分類特徵提取的不直觀性。本文還採用了支持向量機（ svm ）和聚類二叉樹相結合的方法對機器人手預抓取八類模式進行分類，解決了預抓取模式分類訓練速度過慢以及在分類中樣本數量偏少而影響分類效果的問題，得到了較高的正確率。本文對預抓取幾何形狀規則的物體採用直接提取其幾何特徵，對于預抓取幾何形狀不規則的物體採用圖像分析的方法進行特徵提取。
  4. Classification and codes for forestry resources - injurious tree - insects

    林業資源分類與代碼林木害蟲
  5. For classifying unknown 3 - d objects into a set of predetermined object classes, a part - level object classification method based on the improved interpretation tree is presented

    摘要為了實現對未知物體的分類，提出了一種基於改進解釋樹的部件級三維物體分類方法。
  6. The essence of edid is to set up a normal behavior fuzzy sub collection a on the basis of watching the normal system transfer of the privilege process, and set up a fuzzy sub collection b with real time transfer array, then detect with the principle of minimum distance in fuzzy discern method the innovation point of this paper is : put forward the method of edid, can not only reduce efficiently false positive rate and false negative rate, also make real time intrusion detection to become possibility ; have independent and complete character database, according to the classification of monitoring program, design normal behavior and anomaly behavior etc., have raised the strongness of ids ; use tree type structure to preservation the character database, have saved greatly stock space ; in detection invade, carry out frequency prior principle, prior analysis and handling the behavior feature of high frequency in information table, have raised efficiency and the speed of detection, make real time intrusion detection to become possibility ; have at the same time realized anomaly intrusion detection and misuse intrusion detection, have remedied deficiency of unitary detection method

    這種方法的實質是在監控特權進程的正常系統調用基礎上建立正常行為模糊子集a ，用檢測到的實時調用序列建立模糊子集b ，然後用模糊識別方法中的最小距離原則進行檢測。本文的創新點是：通過對特權進程的系統調用及參數序列的研究，提出了基於euclidean距離的入侵檢測方法edid ，不僅能有效降低漏報率和誤報率，而且使實時入侵檢測成為可能；設計有獨立而完整的特徵數據庫，根據被監控程序的類別，分別設計正常行為、異常行為等，提高了檢測系統的強健性和可伸縮性；特徵數據庫按樹型結構存儲，大大節省了存儲空間；在檢測入侵時，實行頻度優先原則，優先分析和處理信息表中的高頻度行為特徵，提高檢測的速度和效率，使實時入侵檢測成為可能；同時實現了異常入侵檢測和誤用入侵檢測，彌補了單一檢測方法的不足。
  7. Therefore, the author established a intellectualized exhumation system basing on classification id3 decision - making tree arithmetic, and provided a valuable example for developing other data exhumation applying system

    因此，基於分類id3決策樹演算法，作者建立了一個智能挖掘體系，並為開發其它數據挖掘應用系統提供了一個有價值的實例。
  8. Decision tree classification algorithm based on bayesian method

    基於貝葉斯方法的決策樹分類演算法
  9. This paper is a study on decision tree classification algorithms, which mainly includes two parts

    本文主要對決策樹分類演算法展開研究，主要包含兩個內容： 1
  10. Secondly, decision tree classification model and logistic regression model are performed to rock mass quality assessment, based on sas / enterprise miner

    應用sas enterpriseminer系統的決策樹分類演算法和logistic回歸演算法進行巖體的質量分級評價。
  11. 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 ） 。
  12. At the stage of image recognition, a unique model of pcb fault recognition was built on methods of tree - classification and sequenntial probability ratio test, and a kind of method of m feature selection and extraction was introduced

    在圖像識別中，本文分析了常用的模式識別方法，根據樹分類法和序貫概率比檢定法的思想設計了一種獨特的pcb缺陷模式識別方法；並給出了針對各種pcb缺陷模式的特徵選擇與提取方法。
  13. Tt _ dtc realizes a series of processes including data preprocess, decision tree classification, producing rules and prediction analysis, which based on the data of train tickets and aimed at the characters of tram tickets which have large amount of data and complex attributes

    Tt _ dtc方法以鐵路客票數據為基礎，以鐵路客票營銷分析為目的，針對鐵路客票信息數據量大、屬性復雜、域值廣等特點，實現了從數據預處理、決策樹生成到規則提取、知識產生等一系列過程。
  14. In the first part, two decision tree classification algorithms, sliq and sprint, is studied, because they are the most useful at present

    研究了sliq演算法和sprint演算法。因為這兩個演算法可以說是目前決策樹演算法中最有效的。
  15. A further study has been made about decision tree classification, bayesian network, and discretization of conntinuous attributes, at the same time many kinds of classfication algorithms have been achieved

    對決策樹分類、貝葉斯網路和連續屬性的離散化問題進行了的研究，實現了多種分類演算法。
  16. When we design the classification, we combine the tree classification and the support vector machines in order to improve the ability of combining experiences and performance of generalization

    在模式識別的分類器設計上，我們採用了樹分類器和支持向量機相結合的方法，提高了分類器經驗結合的能力和泛化能力。
  17. We also make plenty of classification experiments with data sets from various of different fields, and then analyse and compare the classification capacity of several decision tree classification algorithms and the adaptability to different datas

    在來自不同領域的數據集上進行了大量的分類實驗，分析和比較了多種決策樹分類演算法的分類性能和對不同數據的適應性。
  18. The algorithm of sf _ dt, which bases on the idea of decision tree classification algorithm ids, use the means of file splitting take the place of the means which bases on memory. it improves the scalability of classification algorithm and can deal with very large database

    Sf _ dt演算法以決策樹分類演算法id3的基本思想為基礎，用基於文件分割的方法代替原有的基於內存的演算法，提高了演算法的可規模性，可以處理超大規模的數據。
  19. 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

    為進行客戶關系管理，本文基於廣義計算思想，將多準則神經網路和一種決策樹? ?分類回歸樹相結合，提出了一種新的異動客戶識別模型。
  20. With rich data hi tram tickets system, how to mine useful knowledge is an important problem. applying the technology of classification hi train tickets analysis, we construct a new classification method tt _ dtc ( decision tree classification based on train tickets ). we apply new classification algorithm sf _ dt ( decision tree classification algorithm based on splitting files ) that bases on splitting files and quantity rules, which aimed at the characters of train tickets

    本文將數據挖掘中的分類技術用於鐵路客票營銷分析中的客票分類，形成了一種新的分類方法tt _ dtc （ decisiontreeclassificationbasedontraintickets ） ，該方法針對鐵路客票的實際特點，採用新的基於文件分割和定量規則的決策樹分類演算法sf _ dt （ decisiontreeclassificationalgorithmbasedonsplittingfiles ）對客票數據進行分析，以達到依據客票屬性特徵對客票發售及列車運營情況進行分類及預測的目的。
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