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Decision tree

Xem 1-20 trên 153 kết quả Decision tree
  • Đồ án tốt nghiệp: Nghiên cứu Datamining microsoft server 2005 với thuật toán microsoft association rules và microsoft decision tree trình bày về khái niệm khai thác dữ liệu; các thuật toán khai thác dữ liệu; decision tree; định hướng phát triển. Mời các bạn tham khảo.

    pdf82p congtratct91 12-03-2015 104 13   Download

  • Bài giảng Khai mở dữ liệu: Phương pháp học cây quyết định (Decision Tree) giới thiệu về cây quyết định, giải thuật học của cây quyết định, kết luận và hướng phát triển. Mời các bạn tham khảo bài giảng để hiểu rõ hơn về điều này.

    pdf39p maiyeumaiyeu27 10-01-2017 113 11   Download

  • This paper describes novel and practical Japanese parsers that uses decision trees. First, we construct a single decision tree to estimate modification probabilities; how one phrase tends to modify another. Next, we introduce a boosting algorithm in which several decision trees are constructed and then combined for probability estimation. The two constructed parsers are evaluated by using the EDR Japanese annotated corpus. The single-tree method outperforms the conventional .Japanese stochastic methods by 4%. ...

    pdf7p bunrieu_1 18-04-2013 31 5   Download

  • In the face of sparsity, statistical models are often interpolated with lower order (backoff) models, particularly in Language Modeling. In this paper, we argue that there is a relation between the higher order and the backoff model that must be satisfied in order for the interpolation to be effective. We show that in n-gram models, the relation is trivially held, but in models that allow arbitrary clustering of context (such as decision tree models), this relation is generally not satisfied. ...

    pdf5p hongdo_1 12-04-2013 33 4   Download

  • This paper discusses a decision-tree approach to the problem of assigning probabilities to words following a given text. In contrast with previous decision-tree language model attempts, an algorithm for selecting nearly optimal questions is considered. The model is to be tested on a standard task, The Wall Street Journal, allowing a fair comparison with the well-known trigram model.

    pdf4p bunrieu_1 18-04-2013 51 4   Download

  • Syntactic natural language parsers have shown themselves to be inadequate for processing highly-ambiguous large-vocabulary text, as is evidenced by their poor performance on domains like the Wall Street Journal, and by the movement away from parsing-based approaches to textprocessing in general. In this paper, I describe SPATTER, a statistical parser based on decision-tree learning techniques which constructs a complete parse for every sentence and achieves accuracy rates far better than any published result. ...

    pdf8p bunmoc_1 20-04-2013 48 3   Download

  • This paper presents a decision-tree approach to the problems of part-ofspeech disambiguation and unknown word guessing as they appear in Modem Greek, a highly inflectional language. The learning procedure is tag-set independent and reflects the linguistic reasoning on the specific problems. The decision trees induced are combined with a highcoverage lexicon to form a tagger that achieves 93,5% overall disambiguation accuracy.

    pdf8p bunthai_1 06-05-2013 35 3   Download

  • Chapter 5: Decision trees Introduction to decision tree; Decision tree for pattern recognition; Construction of decision trees; Splitting at the nodes; Overfitting and pruning; Example of decision tree induction.

    ppt30p cocacola_10 08-12-2015 57 1   Download

  • Microarray technology can acquire information about thousands of genes simultaneously. We analyzed published breast cancer microarray databases to predict five-year recurrence and compared the performance of three data mining algorithms of artificial neural networks (ANN), decision trees (DT) and logistic regression (LR) and two composite models of DT-ANN and DT-LR.

    pdf11p viwyoming2711 16-12-2020 9 1   Download

  • The precise data classification cannot solve all the requirements. Thus, the fuzzy decision tree classification problem is important for the fuzzy data mining problem. The fuzzy decision classification based on the fuzzy set theory has some limitations derived from its innerself. The hedge algebra with many advantages has become a really useful tool for solving the fuzzy decision tree classification.

    pdf14p thuyliebe 04-10-2018 19 0   Download

  • In this paper, we propose a Learnable Model for Anomaly Detection (LMAD), as an ensemble real-time intrusion detection model using incremental supervised machine learning techniques. Such techniques are utilized to detect new attacks. The proposed model is based on making use of two different machine learning techniques, namely, decision trees and attributional rules classifiers.

    pdf9p byphasse043256 21-03-2019 23 0   Download

  • This paper presents a machine learning approach for assessing the reliability of protein–protein interactions in a high-throughput dataset. We use an alternating decision tree algorithm to distinguish true interacting protein pairs from noisy high-throughput data using various biological attributes of interacting proteins.

    pdf10p vititan2711 13-08-2019 8 0   Download

  • Proposing a model to classify by fuzzy decision trees and a method to select the feature training samples set for classification process. Recommending the linguistic value treatment method of inhomogeneous attributes based on hedge algebra. Proposing the algorithms by fuzzy decision tree in order to be effective in predicting and simple for users.

    pdf26p gaocaolon6 30-07-2020 23 0   Download

  • Systematic approaches to making decisions in the public sector are becoming very common. Most often, these approaches concern expert decision models. The expansion of the idea of the development of e-participation and e-democracy was influenced by the development of technology. All stakeholders are supposed to participate in decision making, so this brings a new feature to the decision-making process, in which amateurs and non-specialists are participating decision making instead of experts.

    pdf20p vinguyentuongdanh 19-12-2018 15 0   Download

  • In this paper, AdaBoost algorithm, a popular and effective prediction method, is applied to predict the prediction of claim frequency of auto insurance, which plays an important part of property insurance companies. Using a real dataset of car insurance, we reduce the frequency prediction problem to be a multi-class problem, in turn we employ the mixed method called multi-class AdaBoost tree (a combination of decision tree with adaptive boosting) as our predictor.

    pdf9p cothumenhmong4 24-03-2020 7 0   Download

  • The most effective way to combat b-thalassemias is to prevent the birth of children with thalassemia major. Therefore, a cost-effective screening method is essential to identify b-thalassemia traits (BTT) and differentiate normal individuals from carriers.

    pdf8p partimesinhvien 08-05-2020 13 0   Download

  • In this paper, we are using three input attributes of training data set quoted by LB, AC, and FM to categorize as normal, suspect or pathological where NSPF variable is used as response variable. After drawing necessary analyzing into three variables we get the 19 nodes of classi cation tree and also we have measured every single node according to statistic, criterion, weights and values. The Cardiotocography Dataset applied in this study are received from UCI Machine Learning Repository.

    pdf10p nguathienthan9 08-12-2020 4 0   Download

  • Cây quyết định (decision tree) là một trong những hình thức mô tả dữ liệu trực quan nhất, dễ hiểu nhất đối với người dùng. Cấu trúc của một cây quyết định bao gồm các nút và các nhánh. Nút dưới cùng được gọi là nút lá, trong mô hình phân lớp dữ liệu chính là các giá trị của các nhãn lớp (gọi tắt là nhãn). Các nút khác nút lá được gọi là các nút con, đây còn là các thuộc tính của tập dữ liệu, hiển nhiên các thuộc tính này...

    pdf70p ruavanguom 18-11-2012 625 115   Download

  • Bài 3 cung cấp cho người học những kiến thức về cây quyết định (Decision tree learning). Trong bài này người học có thể tìm hiểu một số nội dung sau: Định nghĩa, giới thiệu về cây quyết định; biểu diễn mô hình/giả thuyết bằng DT, Khả năng ứng dụng của DT, giải thuật học cơ bản,...và một số nội dung khác.

    pdf36p youcanletgo_04 17-01-2016 53 13   Download

  • Given a collection of records (training set ) Each record contains a set of attributes, one of the attributes is the class. Find a model for class attribute as a function of the values of other attributes. Goal: previously unseen records should be assigned a class as accurately as possible. A test set is used to determine the accuracy of the model. Usually, the given data set is divided into training and test sets, with training set used to build the model and test set used to validate it.

    ppt101p trinh02 18-01-2013 77 10   Download

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