• 제목/요약/키워드: Recursive tree

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연속형 자료에 대한 나무형 군집화 (Tree-structured Clustering for Continuous Data)

  • 허명회;양경숙
    • 응용통계연구
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    • 제18권3호
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    • pp.661-671
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    • 2005
  • 본 연구는 반복분할(recursive partitioning)에 의한 군집화 방법을 개발하고 활용 예를 보인다. 노드 분리 기준으로는 Overall R-Square를 채택하였고 실용적인 노드 분리 결정 방법을 제안하였다. 이 방법은 연속형 자료에 대하여 나무 형태의 해석하기 쉬운 단순한 규칙을 제공하면서 동시에 변수선택기능을 제공한다. 환용 예로서 Fisher의 붓꽃데이터와 Telecom 사례에 적용해 보았다. K-평균 군집화와 다른 몇 가지 사항이 관측되었다.

연속형 자료에 대한 나무형 군집화

  • 허명희;양경숙
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2005년도 춘계 학술발표회 논문집
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    • pp.49-51
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    • 2005
  • 본 연구는 반복분할(recursive partitioning)에 의한 군집화 방법을 제안하고 활용 예를 제시한다. 이 방법은 나무 형태의 해석하기 쉬운 단순한 규칙을 제공하면서 동시에 변수선택기능을 제공한다.

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스도쿠 풀이에서 욕심쟁이 기법과 가지치기를 이용한 완전이진트리 생성 기법 (A Method to Expand a Complete Binary Tree using Greedy Method and Pruning in Sudoku Problems)

  • 김태석;김종수
    • 한국멀티미디어학회논문지
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    • 제20권4호
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    • pp.696-703
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    • 2017
  • In this paper, we show how to design based on solving Sudoku problem that is one of the NP-complete problems like Go. We show how to use greedy method which can minimize depth based on tree expansion and how to apply heuristic algorithm for pruning unnecessary branches. As a result of measuring the performance of the proposed method for solving of Sudoku problems, this method can reduce the number of function call required for solving compared with the method of heuristic algorithm or recursive method, also this method is able to reduce the 46~64 depth rather than simply expanding the tree and is able to pruning unnecessary branches. Therefore, we could see that it can reduce the number of leaf nodes required for the calculation to 6 to 34.

근거리 힘 계산의 새로운 고속화 방법 (A New Fast Algorithm for Short Range Force Calculation)

  • 안상환;안철오
    • 유체기계공업학회:학술대회논문집
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    • 유체기계공업학회 2006년 제4회 한국유체공학학술대회 논문집
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    • pp.383-386
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    • 2006
  • In this study, we propose a new fast algorithm for calculating short range forces in molecular dynamics, This algorithm uses a new hierarchical tree data structure which has a high adaptiveness to the particle distribution. It can divide a parent cell into k daughter cells and the tree structure is independent of the coordinate system and particle distribution. We investigated the characteristics and the performance of the tree structure according to k. For parallel computation, we used orthogonal recursive bisection method for domain decomposition to distribute particles to each processor, and the numerical experiments were performed on a 32-node Linux cluster. We compared the performance of the oct-tree and developed new algorithm according to the particle distributions, problem sizes and the number of processors. The comparison was performed sing tree-independent method and the results are independent of computing platform, parallelization, or programming language. It was found that the new algorithm can reduce computing cost for a large problem which has a short search range compared to the computational domain. But there are only small differences in wall-clock time because the proposed algorithm requires much time to construct tree structure than the oct-tree and he performance gain is small compared to the time for single time step calculation.

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Wage Determinants Analysis by Quantile Regression Tree

  • Chang, Young-Jae
    • Communications for Statistical Applications and Methods
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    • 제19권2호
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    • pp.293-301
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    • 2012
  • Quantile regression proposed by Koenker and Bassett (1978) is a statistical technique that estimates conditional quantiles. The advantage of using quantile regression is the robustness in response to large outliers compared to ordinary least squares(OLS) regression. A regression tree approach has been applied to OLS problems to fit flexible models. Loh (2002) proposed the GUIDE algorithm that has a negligible selection bias and relatively low computational cost. Quantile regression can be regarded as an analogue of OLS, therefore it can also be applied to GUIDE regression tree method. Chaudhuri and Loh (2002) proposed a nonparametric quantile regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning. Lee and Lee (2006) investigated wage determinants in the Korean labor market using the Korean Labor and Income Panel Study(KLIPS). Following Lee and Lee, we fit three kinds of quantile regression tree models to KLIPS data with respect to the quantiles, 0.05, 0.2, 0.5, 0.8, and 0.95. Among the three models, multiple linear piecewise quantile regression model forms the shortest tree structure, while the piecewise constant quantile regression model has a deeper tree structure with more terminal nodes in general. Age, gender, marriage status, and education seem to be the determinants of the wage level throughout the quantiles; in addition, education experience appears as the important determinant of the wage level in the highly paid group.

ALGORITHMIC PROOF OF MaxMult(T) = p(T)

  • Kim, In-Jae
    • 대한수학회논문집
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    • 제27권4호
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    • pp.665-668
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    • 2012
  • For a given graph G we consider a set S(G) of all symmetric matrices A = [$a_{ij}$] whose nonzero entries are placed according to the location of the edges of the graph, i.e., for $i{\neq}j$, $a_{ij}{\neq}0$ if and only if vertex $i$ is adjacent to vertex $j$. The minimum rank mr(G) of the graph G is defined to be the smallest rank of a matrix in S(G). In general the computation of mr(G) is complicated, and so is that of the maximum multiplicity MaxMult(G) of an eigenvalue of a matrix in S(G) which is equal to $n$ - mr(G) where n is the number of vertices in G. However, for trees T, there is a recursive formula to compute MaxMult(T). In this note we show that this recursive formula for MaxMult(T) also computes the path cover number $p$(T) of the tree T. This gives an alternative proof of the interesting result, MaxMult(T) = $p$(T).

Problem Solving Path Algorithm in Distance Education Environment

  • Min, Youn-A
    • 한국컴퓨터정보학회논문지
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    • 제26권6호
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    • pp.55-61
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    • 2021
  • 원격교육에서 학습자의 효율적 학습을 지원하기 위하여 학습추적 알고리즘을 통한 문제해결 경로 제시가 필요하다. 본 논문에서는 기존 학습추적 알고리즘을 보완하여 다양한 과목에서 다양한 난이도의 문제 해결경로를 제안하였다. 학습자의 문제해결을 위한 경로를 통하여 얻은 데이터 셋을 통하여 프림 최소비용신장트리를 통한 경로를 확보하고 해당 Path 데이터셋을 통하여 재귀신경망을 통한 최적의 문제해결 경로를 제시하도록 하였다. 본 논문에서 제안한 내용에 대한 성능평가 결과 실험대상자 52% 이상이 문제해결 과정에서 제안한 문제해결 경로를 포함하였으며 문제해결 시간 역시 45% 이상 향상된 것을 확인하였다.

프랙탈 트리를 이용한 자동 작곡 방법 (Automatic Composition Algorithm based on Fractal Tree)

  • 곽성호;유민준;이인권
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2008년도 학술대회 1부
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    • pp.618-622
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    • 2008
  • 본 논문에서는 프랙탈 이론을 이용한 새로운 자동 작곡 알고리즘을 제안한다. 사용자는 L-System에서 시작 상태 및 생성 규칙들을 설정함으로써 다양한 프랙탈 형태를 정의 및 조정할 수 있다. 본 연구에서는 먼저 L-System과 확률을 이용하여 비대칭인 프랙탈 트리를 생성한다. 그리고 생성된 프랙탈 트리의 이미지를 기반으로 음악화 기법을 이용하여 음악을 생성한다. 본 논문에서는 다음 두 가지 방법을 소개한다. 첫째로, 이미지의 x축과 y축을 음의 크기와 음정으로 매핑하여 단선율 음악을 생성한다. 둘째로, 이미지의 x축과 y축을 시간과 음정으로 매핑하여 다성음악을 생성한다. 본 논문에서 제시하는 방법을 이용하여 사용자는 프랙탈의 재귀적인 특징이 반복성으로 나타나는 음악을 생성할 수 있으며, 프랙탈 트리의 모습을 음악적 구조로 갖는 음악을 생성할 수 있다.

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Simple Recursive Approach for Detecting Spatial Clusters

  • Kim Jeongjin;Chung Younshik;Ma Sungjoon;Yang Tae Young
    • Communications for Statistical Applications and Methods
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    • 제12권1호
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    • pp.207-216
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    • 2005
  • A binary segmentation procedure is a simple recursive approach to detect clusters and provide inferences for the study space when the shape of the clusters and the number of clusters are unknown. The procedure involves a sequence of nested hypothesis tests of a single cluster versus a pair of distinct clusters. The size and the shape of the clusters evolve as the procedure proceeds. The procedure allows for various growth clusters and for arbitrary baseline densities which govern the form of the hypothesis tests. A real tree data is used to highlight the procedure.

Quadtree를 이용한 절삭 영역 탐색 기법에 관한 연구 (Research of Searching Algorithm for Cutting Region using Quadtree)

  • 김용현;고성림;이상규
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2003년도 춘계학술대회 논문집
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    • pp.873-876
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    • 2003
  • Z-map model is the most widely used model for NC simulation and verification. But it has several limitations to get a high precision, to apply 5 axis machining simulation. In this paper, we tried to use quadtree for searching cutting region. Quadtree representation of two dimensional objects is performed with a tree that describes the recursive subdivision. By using these quadtree model. storage requirements were reduced. And also, recursive subdivision was processed in the boundries, so, useless computation could be reduced, too. To get more high Accuracy, we applied the supersampling method in the boundaries. The Supersampling method is the most common form of the antialiasing and usually used with polygon mesh rendering in computer graphics To verify quadtree model we compared simulated results with z-map model and enhanced z-map model

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