• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.539-551
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• 2004

Multiple responses are often observed in many application fields, such as customer's time-of-day pattern for using internet. Some decision trees for multiple responses have been constructed by many researchers. However, if the response is a high-dimensional vector that can be thought of as a discretized function, then fitting a multivariate decision tree may be unsuccessful. Yu and Lambert (1999) suggested spline tree and principal component tree to analyze high dimensional response vector by using dimension reduction techniques. In this paper, we shall propose factor tree which would be more interpretable and competitive. Furthermore, using Korean internet company data, we will analyze time-of-day patterns for internet user.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.4-6
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• 2006

Tree-dependent component analysis (TCA) is a generalization of independent component analysis (ICA), the goal of which is to model the multivariate data by a linear transformation of latent variables, while latent variables fit by a tree-structured graphical model. In contrast to ICA, TCA allows dependent structure of latent variables and also consider non-spanning trees (forests). In this paper, we present a TCA-based method of clustering gene expression data. Empirical study with yeast cell cycle-related data, yeast metaboiic shift data, and yeast sporulation data, shows that TCA is more suitable for gene clustering, compared to principal component analysis (PCA) as well as ICA.

• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.517-528
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• 2018

We provide R scripts to detect outliers in multivariate data and visualization. Detecting outliers is provided using three approaches 1) Robust Mahalanobis distance, 2) High Dimensional data, 3) density-based approach methods. We use the following techniques to visualize detected potential outliers 1) multidimensional scaling (MDS) and minimal spanning tree (MST) with k-means clustering, 2) MDS with fviz cluster, 3) principal component analysis (PCA) with fviz cluster. For real data sets, we use MLB pitching data including Ryu, Hyun-jin in 2013 and 2014. The developed R scripts can be downloaded at "http://www.knou.ac.kr/~sskim/ddpoutlier.html" (R scripts and also R package can be downloaded here).

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.317-322
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• 2011

Korean adults' internet addiction diagnosis measure, K-scale developed by Korea National Information Society Agency (NIA), has composed of 4 categories including 20 items. This scale can diagnose user's internet addiction with individual's questionnaire items. Most of previous research works were tried to know reasons of internet addiction and to judge whether adolescents are addicted or not with their samples. In this research, it is the goal to find the key component to judge individual's internet addiction by using a decision tree in the data mining field and a principal component analysis in statistics. From the experimental results, we would discover that tolerance and preoccupation factor is the most important one to affect adult's internet addiction.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.167-171
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• 2005

마이크로어레이자료의 분석에 있어서 주성분 자기조직도(principal component SOM)의 유용성을 알아보고, 흔히 사용되는 다른 군집분석방법과 비교하였다. 또한 MST(minimal spanning tree)를 이용하여 주성분자기조직도 결과의 적합성을 알아보았다.

• Journal of Forest and Environmental Science
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• v.37 no.1
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• pp.35-43
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• 2021

The interspecific hybrid of Salix caprea and Salix gracilistyla has never been identified or studied in Korea. Accordingly, this study investigated the flower morphological characteristics of the interspecific hybrid between S. caprea and S. gracilistyla and compared the interspecific hybrid with S. caprea and S. gracilistyla, respectively. The female flowers were investigated for 12 characteristics and the male flowers were investigated for nine. For the female flowers, those of the hybrids were larger than those of S. caprea and S. gracilistyla in terms of catkin length (CL), bract length (BL), and bract width (BW). The hybrids are intermediates between S. caprea and S. gracilistyla in terms of ovary length, width, and stipitate length as well as gland length (GL). For the male flowers, those of the hybrids were bigger than those of S. caprea and S. gracilistyla in terms of CL, BL, and BW. The hybrids are intermediates between S. caprea and S. gracilistyla in terms of catkin width and stamen length (SL). A principal component analysis (PCA) of the female data showed that the first principal component (PC) explained 57.5% of the total variation. The first PC highly correlated the ovary stipitate and pistil style lengths. The analysis was divided into three groups of S. caprea, S. gracilistyla, and the hybrid by the first PC. The results of a PCA of the male data showed that the first PC explained 35.7% of the total variation. The first PC highly correlated with the adelphous SL and was divided into three groups of S. caprea, S. gracilistyla, and the hybrid. The results of the discriminant analysis showed that S. caprea, S. gracilistyla, and the hybrid were distinguishable by flower morphological characteristics. Therefore, the hybrid was distinctly separated from S. caprea and S. gracilistyla by flower characteristics.

• Journal of Power Electronics
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• v.8 no.1
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• pp.101-107
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• 2008

In this paper, the features extracted from vibration time signals are used to detect the bearing fault condition. The decision tree is applied to diagnose the bearing status, which has the benefits of being an expert system that is based on knowledge history and is simple to understand. This paper also suggests a genetic algorithm (GA) as a method to reduce the number of features. In order to show the potentials of this method in both aspects of accuracy and simplicity, the reduced-feature decision tree is compared with the non reduced-feature decision tree and the PCA-based decision tree.

• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.877-885
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• 2004

In this paper, we propose an enhancement shot change detection method using the neural net and the robust feature selection out of multiple features. The previous shot change detection methods usually used single feature and fixed threshold between consecutive frames. However, contents such as color, shape, background, and texture change simultaneously at shot change points in a video sequence. Therefore, in this paper, we detect the shot changes effectively using robust features, which are supplementary each other, rather than using single feature. In this paper, we use the typical CART (classification and regression tree) of data mining method to select the robust features, and the backpropagation neural net to determine the threshold of the each selected features. And to evaluation the performance of the robust feature selection, we compare the proposed method to the PCA(principal component analysis) method of the typical feature selection. According to the experimental result. it was revealed that the performance of our method had better that than the PCA method.

• Journal of Forest and Environmental Science
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• v.32 no.4
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• pp.367-376
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• 2016

Urban greenery is an important component of urban environment and is fast gaining prominence especially in the developing countries. The destruction of urban trees has resulted to the degradation of the environment, thus the introduction of green Kumasi project by Kumasi Metropolitan Assembly, Ashanti Region of Ghana. The composition and diversity of urban trees gives rise to adequate management and monitoring, thus an inventory of urban trees of the Metropolis was conducted to document complete information on its density, diversity, composition and distribution. A total tree population of 1,101 was enumerated in the principal roads of the Metropolis. The ten most encountered tree species accounted for 61.04% of all the individual tree populations with Mangifera indica being dominant. The dominant families: Fabaceae, Moraceae and Arecaceae constitute 38.57% of the tree population. Diversity of the tree species was very high. The minimum diversity criteria were met on analysis of the diversity of this population. The proportion of exotic species was high with 65.71% of the trees belonging to the introduced species. It is recommended that greater emphasis should be placed on the planting of indigenous trees in future tree planting exercise.

• Journal of Korean Society of Forest Science
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• v.78 no.3
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• pp.255-262
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• 1989

Vegetation data of the mixed mesophytic forest in Mt. Chombong area were analyzed by the methods of classification and ordination. 'Weighted group average linkage cluster analysis' recognized five distinctive vegetation groups, based on the abundance data of 83 woody plant species in 70 sampling units. The species diversity was also examined for each group. The importance values of 42 tree species in the groups were subjected to principal component analysis (PCA). The PCA ordinated five vegetation groups on the first two axes, so as to compare similarity among them in terms of species composition. Acer palmatum, Fraxinus rhynchophylla, Quercus mongolica, and Acer mono had greatest influence on the determination of group scores with high eigenvectors (component loadings) in the first axis. Distribution of these four dominant species appeared to be important in determining community association in this diversified forest.