decision tree system 中文意思是什麼
decision tree system
解釋
決策樹系統-
According to the assessment & acceptance management characteristics and demands of s & t project in china, this paper discusses and builds the index system of s & t project assessment & acceptance, depicts the stage assessment & acceptance methods, and then constructs the decision model based on c4. 5 decision tree method
根據我國目前科技項目驗收評估管理的特點和要求，討論並建立了科技項目驗收評估的指標體系，闡述了分階段的科技項目驗收評估方法，建立了基於c4 . 5決策樹科技項目驗收評估決策模型。 -
The features of aircraft flight line maintenance expert system were analyzed in this dissertation. decision fault tree ( dft ) based binary decision diagram ( bdd ) was presented, which applied in the expert system in combination with case based reasoning ( cbr )
本文分析了飛機航線維護排故專家系統的特點，提出了基於二元決策圖的判定故障樹方法，並將該方法和基於事例推理的方法應用於專家系統的開發，給出了這兩種方法的集成診斷模型。 -
Developing from the typical decision tree learning system ids and using the idea of weight sum, we did exploring research on the application of decision tree technology, using weight entropy to get predicted attribute and division value, in crm of tourism industry
在典型的決策樹學習系統id3之上，利用「加權和」的思想，在對決策樹技術（使用加權熵來獲得預測屬性和分裂值）在旅遊crm中應用上作了探索性研究。 -
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。 -
Network forensics is an important extension to present security infrastructure, and is becoming the research focus of forensic investigators and network security researchers. however many challenges still exist in conducting network forensics : the sheer amount of data generated by the network ; the comprehensibility of evidences extracted from collected data ; the efficiency of evidence analysis methods, etc. against above challenges, by taking the advantage of both the great learning capability and the comprehensibility of the analyzed results of decision tree technology and fuzzy logic, the researcher develops a fuzzy decision tree based network forensics system to aid an investigator in analyzing computer crime in network environments and automatically extract digital evidence. at the end of the paper, the experimental comparison results between our proposed method and other popular methods are presented. experimental results show that the system can classify most kinds of events ( 91. 16 ? correct classification rate on average ), provide analyzed and comprehensible information for a forensic expert and automate or semi - automate the process of forensic analysis
網路取證是對現有網路安全體系的必要擴展，已日益成為研究的重點.但目前在進行網路取證時仍存在很多挑戰:如網路產生的海量數據;從已收集數據中提取的證據的可理解性;證據分析方法的有效性等.針對上述問題，利用模糊決策樹技術強大的學習能力及其分析結果的易理解性，開發了一種基於模糊決策樹的網路取證分析系統，以協助網路取證人員在網路環境下對計算機犯罪事件進行取證分析.給出了該方法的實驗結果以及與現有方法的對照分析結果.實驗結果表明，該系統可以對大多數網路事件進行識別（平均正確分類率為91 . 16 ? ） ，能為網路取證人員提供可理解的信息，協助取證人員進行快速高效的證據分析 -
It ' s a pity that although there are many papers and articles focused on data mining published every year, most of them deal with data mining concept and abstract algorithm theory, it is hardly to see their real implementation and application, in this context, when i was in my graduate exercitation in a company in beijing, which focus on developing supermarket software, i joined and completed an olap ( online analytical processing ) project, merchandise analysis and sale report system, which based on microsoft analysis service and microsoft sql server. i also design and implement three important algorithms : merchandise association rule algorithm based on multi - level merchandise category, supermarket member customer shopping frequent sequence generating algorithm, customer classification ( decision tree ) algorithm which based on information entropy and conditional probability tree, and they all achieve expected result
本文作者在實習期間，參與並完成了基於微軟分析服務器的銷售分析與報表系統；並在公司即將開始的數據挖掘項目中，完成了多個重要演算法的設計和c + +程序實現：基於多層分類商品樹的商品關聯規則演算法，會員顧客的購物頻繁序列模式產生演算法；基於信息熵理論和條件概率樹的會員顧客分類（決策樹）演算法，並分別使用數據進行了測試，取得了較好的結果。 -
Just as most of the natural language process technologies, the methods of ner have two classes, statistic - based and rule - based. considering of the limitation of using only one of the methods, we combined both of the methods to recognize named entity in this thesis. we combined the maching learning with ner to make the system get the ability of self - learning. we have done research on decision tree of maching learning mainly and designed a recognize model to recognize named entity. this model first used the probability and statistic way to extract the potential named entities, and then some context linguistic language information are employed in the model to recognize the named entities furtherly. as the wrong entites are denied, the recongnize effect has been improved
鑒于單獨採用基於統計方法或基於規則方法的缺陷，在這篇論文中，採用了統計與規則相結合的方法來識別命名實體。為了使系統具有學習能力，我們把機器學習方法應用於中文命名實體的識別，這里我們著重研究了機器學習中的決策樹方法在中文命名實體識別中的應用;設計了一種基於決策樹的識別模式，該模式首先利用概率統計方法，在文本中盡量完備地識別出潛在的命名實體，然後利用潛在命名實體相關的上下文詞法、語法和語義特徵作為屬性構建決策樹，否定不正確的實體，進一步提高了命名實體識別的準確率。 -
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 ） 。 -
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。 -
The data mining modeling of a decision tree is studied using the transmission system of a lathe as an example, and the mapping of product conceptual design is primarily achieved
以機床傳動系統為例，研究決策樹演算法的數據挖掘模型，並初步實現了產品概念設計過程的功能結構映射。 -
A model of spatial decision support system based on spatial data mining was established after making research on application and integration of spatial data mining, " 3s " technology and environment model, which include designing of data base, knowledge base, model base and their management system, inference engine and intelligent data mining engine ; 2. a model using artificial neural networks to forecast in coast environment in fujian was established, and a method applying multivariate decision tree to remote sensing classification was presented ; 3. a novel and shortcut method realizing artificial neural networks was presented, and then we put forward method realizing decision tree and realized it in prototype
論文的主要內容概括起來有： （ 1 ）對空間數據挖掘技術、 「 3s 」技術、環境模型在空間決策支持系統中的應用與集成進行了研究，提出了一種基於空間數據挖掘的環境調控空間決策支持系統的模型，包括模型庫及其管理系統、知識庫及其管理系統、數據庫及其管理系統、推理機以及數據挖掘智能引擎等的設計； （ 2 ）建立了人工神經網路在福建省海岸帶環境預測中應用的模型，提出了復合決策樹演算法在遙感分類的應用方法； （ 3 ）提出一種新穎的、簡便快捷的人工神經網路的實現方法，以及決策樹的實現方法，並在原型系統中作了實現。 -
The method is better than others. firstly, the system sets up several models to assist detection work, such as road model, illumination model, shadow model and relationship model among them ; secondly, it introduces hue. saturation degree information to distinguish vehicles from shadow ; thirdly, it makes use of binary decision tree to analyze pressing line of vehicles to improve the reliability of the system ; fourthly, it puts forward a way of one dimension video tracing to resolve the problem of vehicle velocity detection
該方法通過設置在每條車道中的兩條相互垂直的虛擬檢測線來檢測交通流信息（如車流量、車速等） ；設計一種彩色分段檢測技術來提取運動車輛的尺寸信息和色彩信息，再利用分類決策樹和濾波演算法確定運動車輛存在與否，增強了車輛、陰影、噪聲和背景之間的區分能力；設計了一種車速視頻檢測方法。 -
Improved decision tree method for mid - long term load forecasting of power system
電力系統中長期負荷預測的改進決策樹演算法 -
Thirdly, by introducing fuzzy theory into system evaluation, evaluating student, teaching, course resource, and function of whole system. fourthly, making use of learning from examples based on information theory, machine learning algorithm is improved and machine learning decision tree is realized. finally, on reasoning mechanism, combining means of two classes reasoning is taken
第三，在系統評價中引入了模糊理論，對學生、教學、課程資源以及系統的整體功能進行了評價；第四，採用基於信息論的示例學習，改進了決策樹學習演算法，並建立了機器學習決策樹；第五，在推理機制上，採取兩級推理相結合的方法進行推理，即用基於語義網路的模糊推理確定教學序列，用基於產生式規則的推理確定教學方法，並給出了詳細的推理演算法。 -
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。 -
Further more, approach for fdd based on rough set theory and logical fault tree ( lft ) is presented. the feasibility of forming a knowledge discovering and intelligent decision - making system for these a
6 、對下一步在基於粗糙集的過程建模、控制和故障診斷等方面將要進行的工作進行了展望。 -
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。 -
After successful construction of data warehouse system, this thesis crossly applies several theories to combine technologies of neural network and decision tree. thus a model of the analysis of customer chum is built to solve the emerging problem of customer churn from mobile communication companies
在成功構建數據倉庫系統之後，針對移動通信行業日益突出的客戶流失問題，本文採用了多種理論相互融合的思想，將神經網路和決策樹技術相結合，構建客戶流失分析模型。 -
At first, this thesis described the necessary of implementing dm in crm systems at on the basis of explaining the elementary concepts and principles of crm and dm, constructed a crm system framework with the center of dm. then, it ameliorated and expanded the models of traditional association rule and decision tree for classification, put forward association rule with time constraint and fuzzy decision tree for classification. the thesis amended traditional algorithms and showed the application methods of new models
論文首先從客戶關系管理和數據挖掘的基本概念和原理入手，闡明了在客戶關系管理中應用數據挖掘的必要性，構建了以數據挖掘為核心的crm系統框架；然後，論文改進和擴展了傳統的關聯規則和決策分類樹模型，提出了具有確定性時間約束的關聯規則和模糊決策分類樹，並修改了傳統的挖掘演算法，通過示例展示了新模型的應用方法。 -
With the studying of decision tree, the decision tree learning that only can describe the accurate characters is not adapted to the requirement describing the imprecise knowledge of a system. the world human being belong to and the domains issues within are dynamic. so in the real world, we hope the decision tree is capable of describing the dynamic fuzzy issues
隨著決策樹歸納學習研究的深入，具有精確描述特徵的決策樹歸納學習已經不能適應一個系統中不精確的知識表達的要求，同時由於人們所處的世界和問題所在的域都是時刻運動變化的，所以在現實問題中人們更希望決策樹能夠描述具有動態模糊性的問題。
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