decision-tree structure 中文意思是什麼
decision-tree structure
解釋
樹形判定結構-
The thesis is based on income question, forest coverage rate and grop production. to beging with, date envelopment analysis is proved that it can be applicated into grain for green in shan - bei district, and then in view of the fact, seven esential factors which have influence on the project are found out : expense of dam, expense of crop, expense of cash tree, expense of defense tree, other economic crop, expense of grass and graziery ; and the output factors include : income of gdp, pure income per captia, the area of decreasing land loss, graziery income, crop production, income of tree, the totle income of economic crop. after the date of each facts are puted into dea model, unefficiencial decision making units ( dmu ) found. the data that are got through adjusting unefficiencial dmus dy dea can offer guide in shanbei district upgrading of an industrial structure. at the same time, taking into account some possible problems in or after grain for green in shan - bei district, the thesis bring out some propesal to improve the circ umstance, enhance the life level and put the relation of population, resource and circumstance into a healthy orbit
因此，加快退耕還林還草，調整土地利用結構和產業結構，已成為實現山川秀美工程和可持續發展戰略的必經之路。論文以解決陜北地區的收入問題，植被問題以及糧食產量問題為出發點，首先從理論上分析了包絡分析方法在陜北地區退耕還林（草）中運用的可行性，然後結合陜北地區目前的實際情況，綜合分析出影響陜北地區退耕還林（草）的關鍵的七個因素作為輸入指標：水利水保設施投入，農作物投入，經濟林種支出，防護林支出，其它經濟作物，草類支出，畜牧業投入；以退耕還林所要解決的最終問題作為輸出指標： gdp收入、農民人均純收入、水土流失減少量、牧業總產值、糧食產量、林業總產值、其他經濟作物總產值。將各指標所對應的數據代入模型后，通過分析求解得出非有效的決策單元，再運用包絡分析方法的一些基本原理對非有效的決策單元進行調整，由此所得的數據對陜北地區的實際投入具有很好的指導意義。 -
Methods for inducing decision tree in distributed database system are described and a distributed algorithm based on id3 is proposed. using a new data structure called attributes distribution list this algorithm can be scalable and parallelized
該演算法在傳統的id3演算法的基礎上引進了新的數據結構：屬性按類別分佈表，使得演算法具有可伸縮性和并行性。 -
In our research, variation of contour line is used for describing the characteristics of image structure. using teacher images and machine learning method, an image direction classification model is built as a decision tree. test results argued the validity of this method
本課題使用圖像輪廓線向量特徵來反映圖像的構圖特徵，通過教師實例獲得用戶的方向分類概念，然後利用決策樹的學習建立分類模型，並且在此分類模型的基礎上實現了一個圖像正立方向判別系統。 -
Based on the analysis of collaboration net and decision - making tree, a new approach to design organizational structure is advanced : building a hierarchtical structure among decision - makers in an organization is to design the best decision - making tree on the basis of collaboration net
通過對組織協作網與決策樹的描述分析提出了組織結構設計的新思路：基於決策個體在任務上的協作關系設計最佳的決策樹（組織決策的層次結構） 。
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