• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.63
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• pp.23-31
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• 2001

Data mining can be either directed or undirected. One way of thinking about it is that we use undirected data mining to recognize relationship in the data and directed data mining to explain those relationships once they have been found. Several data mining techniques have received considerable research attention. In this paper, we propose an algorithm for discovering association rules as directed data mining and applying them to classification. In the first phase, we find frequent closed itemsets and association rules. After this phase, we construct the decision trees using discovered association rules. The algorithm can be applicable to customer relationship management.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.23.4-23
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• 2001

This paper proposes a new approach to unsupervised classification of remotely sensed images. Fusion of optic images (Landsat TM) and radar data (SAR) has beer used to increase the accuracy of classification. Number of clusters is estimated using generalized Dunns measure. Performance of the proposed method is best observed comparing the classified images with classified aerial images.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.3
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• pp.19-31
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• 2017

Plants are the basis for sustainable green growth, and the value of existence and importance of trees including landscape Plants can't be emphasized enough. Therefore, they are precious living things thriving in all sorts of public services, and continuous civil complaints for justifiable compensation of landscape Plants are filed. First, the standard formula of planting intervals according to production target specifications is calculated using root-collar caliper and diameter at breast height, and apply (1) standard medium sized trees which have not yet reached commercialization [deciduous tree production goal (R(B) less than 6cm]= (target standard)= [target standard $R(cm){\times}15{\times}0.7$]. (2) In case of commercialization(R6~R10)= [target standard $R(cm){\times}15{\pm}5%$], (3) In case of more than R12= [target standard $R(cm){\times}15{\times}130%$] shall be applied. In case of using diameter at breast height (4) In case of commercialization(B6~B10)= [target standard $B(cm){\times}20{\times}15{\pm}5%$], (5) In case of more than B12= [target standard $B(cm){\times}20{\times}130%$] shall be applied. Second, appraisal methods based on tree classification of compensation for loss are classified according to planted locations. (1) landscape trees within a house=[price of arrival at the site+planting cost], (2) landscape trees in places such as arboretum=[management technology of tress + relocation expenses considering scarcity of the trees (3) landscape trees in a place of loads= [landscape tree production cost + work out added price. In case of producted landscape threes (4) landscape trees ready to be commercialized as sales loss.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.183-190
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• 2007

We present a new decision tree classification algorithm using rough set theory that can induce classification rules, the construction of which is based on core attributes and relationship between objects. Although decision trees have been widely used in machine learning and artificial intelligence, little research has focused on improving classification quality. We propose a new decision tree construction algorithm that can be simplified and provides an improved classification quality. We also compare the new algorithm with the ID3 algorithm in terms of the number of rules.

• Journal of Korean Society for Quality Management
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• v.36 no.1
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• pp.72-79
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• 2008

The policy for credit card approval/disapproval is based on the applier's personal and financial information. In this paper, we will analyze 2 credit card approval data with several classification methods. We identify which variables are important factors to decide the approval of credit card. Our main tool is an open-source statistical programming environment R which is freely available from http://www.r-project.org. It is getting popular recently because of its flexibility and a lot of packages (libraries) made by R-users in the world. We will use most widely used methods, LDNQDA, Logistic Regression, CART (Classification and Regression Trees), neural network, and SVM (Support Vector Machines) for comparisons.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.375-381
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• 2014

Data mining is a process of discovering useful patterns or information from large amount of data. Decision tree is one of the data mining algorithms that can be used for both classification and prediction and has been widely used for various applications because of its flexibility and interpretability. Decision trees for classification generally generate a number of rules that belong to one of the predefined category and some rules may belong to the same category. In this case, it is necessary to determine the significance of each rule so as to provide the priority of the rule with users. The purpose of this paper is to propose a rule selection method in classification tree models that accommodate the umber of observation, accuracy, and effectiveness in each rule. Our experiments demonstrate that the proposed method produce better performance compared to other existing rule selection methods.

• Journal of Service Research and Studies
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• v.3 no.1
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• pp.9-16
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• 2013

Data analysis is the universal classification techniques, which requires a lot of effort. It can be easily analyzed to understand the results. Decision tree which is developed by Breiman can be the most representative methods. There are two core contents in decision tree. One of the core content is to divide dimensional space of the independent variables repeatedly, Another is pruning using the data for evaluation. In classification problem, the response variables are categorical variables. It should be repeatedly splitting the dimension of the variable space into a multidimensional rectangular non overlapping share. Where the continuous variables, binary, or a scale of sequences, etc. varies. In this paper, we obtain the coefficients of precision, reproducibility and accuracy of the classification tree to classify and evaluate the performance of the new cases, and through experiments to evaluate.

• Journal of Korean Society of Forest Science
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• v.34 no.1
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• pp.47-56
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• 1977

I have investigated and compared the morphology of vascular bundle shown in the section of culm wall of bamboo trees growing on Mt. Jiri which were classified by Grosser and Liese with their methods of morphological classification. The results obtained were as follows: 1. It was shown that there are no b.g.i. types of bamboo classified by Grosser and Liese among the bamboo trees on Mt. Jiri (Phyllostachys and Sasa). 2. As for the thickness of the culm wall in the culm, it was shown that the culm wall of the Phyllostachys becomes thinner in proportion to its nearness to the upper part of the tree, but no distinctive difference appeared in the Sasa. 3. The c, d, and e types of Sasa were the same as those of the Phyllostachys, but there was a vascular bundle type of the a' type, which was quite different from that of the Phyllostachys. 4. It was shown that the a', d, and e types of Sasa were distributed in a zone less than 500m above sea level, but no a' type was distributed in the high mountain area except for the c, d and e types which ranged from 600m to 1000m above sea level. Such facts mean that the vascular bundle sheath has changed in quantity because of the height of mountain. 5. In general, as compared with the Phyllostachys, the Sasa (types a, c, d and e which included a new type a) have fewer vascular bundles. 6. Considering the above results, it is thought that not by the current Sasa classification method based on observation of the the study of Sasa form the outside, but by a new method of classification based on the aspect of the physiological construction as seen from the inside wall is advanced. I believe this new method of classification to be a first step towards an epoch-making methodological advance and encourage the further study of it.

• Journal of Korean Society of Forest Science
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• v.25 no.1
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• pp.13-47
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• 1975

Among the many species of bamboo, it is well known that the dwarf-type is widely distributed in the tropical regions, and the slender type in temperated zone. In the temperated zone the trees have extensively differentiated into one hundred species in 50 genera. In many oriental countries, the bamboo wood is being used as a material for construction and for the manufacture of technical instruments. The bamboo shoot is also regarded as a good and delicious edible resource. Moreover, recent medical investigation verifies that the sap of certain species of the bamboo is an antibiotic effect against cancer. Fortunately, it is very easy to propagate the bamboo trees by using cutting from southeastern Asian countries. This important resource can further be used as a significant source of pulp, which is becoming increasingly important. The classification system of this significant resource has not been completely established to date, even though its importance has been emphasized. Initiated by Canlevon Linne in the 18th century, a classification method concerning the morphological characteristics of flowers was the first step in developing a classification. But it was not an easy task to accomplish, because this type of classification system is based on the sexual organs in bamboo trees. Because the bamboo has a long life cycle of 60-120 years and classification according to this method was very difficult as the materials for the classification are not abundant and some species have changed, even though many references related to the morphological classification of bamboo trees are available nowadays. So, the certification of bamboo trees according to the morphological classification system is not reasonable for us. Consequently, the classification system of bamboo trees on the basis of endomorphological characteristics was initiated by Chinese-born Liese. And classification method based on the morphological characteristics of the vascular bundle was developed by Grosser. These classification methods are fundamentally related to Holltum's classification method, which stressed the morphology of the ovary. The author investigated to re-establish a new classification method based on the vascular sheath. Twenty-six species in 11 genera which originated from Formosa where used in the study. The results obtained from the investigation were somewhat coordinated with those of Crosser. Many difficulties were found in distinguishing the species of Bambusa and Dendrocalamus. These two species were critically differentiated under the new classification system, which is based on the existence of a separated vascular bundle sheath in the bamboo. According to these results, it is recommended that Babusa divided into two groups by placing it into either subspecies or the lower categories. This recommendation is supported by the observation that the evolutional pattern of the bamboo thunk which is from outward to inward. It is also supported by the viewpoint that the fundamental hypothesis in evolution is from simple to complex. There remained many problems to be solved through more critical examination by comparing the results to those of the classification based on the sexual organs method. The author observed the figure of the cross-sectional area of vascular trunk of bamboo tree and compared the results with those of Grosser and Liese, i.e. A, $B_1$, $B_2$, C, and D groups in classification. Group A and $B_2$ were in accordance with the results of those scholars, while group D showed many differences, Grosser and Liese divided bamboo into "g" type and "h" type according to the vascular bundle type; and they included Dendrocalamus and Bambusa in Group D without considering the type of vascular bundle sheath. However, the results obtained by the author showed that Dendrocalamus and Bambusa are differentiated from each other. By considering another group, "i" identified according to the existence of separated vascular bundle sheath. Bambusa showed to have a separated vascular bundle sheath while Dendrocalamus does not have a separated vascular bundle sheath. Moreover, Bambusa showed peculiar characteristics in the figure of vascular development, i.e., one with an inward vascular bundle sheath and the other with a bivascular bundle sheath (inward and outward). In conclusion, the bamboo species used in this experiment were classified in group D, without any separated vascular bundle sheath, and in group E, with a vascular bundle sheath. Group E was divided into two groups, i.e., and group $E_1$, with bivascular sheath, and group $E_2$, with only an inward vascular sheath. Therefore, the Bambusa in group D as described by Grosser and Liese was included in group E. Dendrocalamus seemed to be the middle group between group $E_l$ and group $E_2$ under this classification system which is summarized as follows: Phyllostachys-type: Group A - Phyllostachys, Chymonobambus, Arundinaria, Pseudosasa, Pleioblastus, Yashania Pome-type: Group $B_2$ - Schizostachyum, Melocanna Hemp-type: Group D - Dendrocalamu Bambu-type: Group $E_1$ - Bambusa ghi.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1409-1411
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• 2003

The application of simulated KOMPSAT-2 imagery to monitor graveyards is to be developed. Positions calculated from image were compared with those obtained from Geographic Positioning System. With 24 checkpoints, the position of graveyards showed within 5-meter range. Unsupervised classification, supervised classification, and objected-orientation classification algorithms were used to extract the graveyard. Unsupervised classification with masking processes based on National topographic data gives the best result. The graveyards were categorized with four types in field studies while the two types of graveyards were shown in descriptive statistics. Cluster Analysis and discriminant analysis showed the consistency with two types of tombs. It was hard to get a specific spectral signature of graveyards, as they are covered with grasses at different levels and shaded from the surrounding trees. The slopes and aspects of location of graveyards did not make any difference in the spectral signatures. This study gives the basic spectral characteristics for further development of objected-oriented classification algorithms and plausibility of KOMPSAT-2 images for management of mountainous areas in the aspect of position accuracy and classification accuracy.