• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.11a
• /
• pp.945-947
• /
• 2013

입력 모듈의 결함경향성을 결정하는 결함 예측 모델 연구들은 대부분 훈련 데이터 집합을 사용하는 감독형 모델에 관련된 것들이었다. 하지만 과거 데이터 집합이 없거나 현재 프로젝트 성격이 다른 경우는 비감독형 모델이 필요하며, 이들에 관한 연구들은 모델 구축의 어려움 때문에 극소수 존재한다. 본 논문에서는 대표적인 클러스터링 알고리즘들을 사용한 비감독형 모델들을 제작하여, 기존 모델들이 많이 사용한 K-means 모델과 나머지 모델들의 성능을 비교하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.3
• /
• pp.151-157
• /
• 2018

Most previous studies of software fault prediction have focused on supervised learning models for binary classification that determines whether an input module has faults or not. However, binary classification model determines only the presence or absence of faults in the module without considering the complex characteristics of the fault, and supervised model has the limitation that it requires a training data set that most development groups do not have. To solve these two problems, this paper proposes severity-based ternary classification model using unsupervised learning algorithms, and experimental results show that the proposed model has comparable performance to the supervised models.

• KIPS Transactions on Software and Data Engineering
• /
• v.3 no.2
• /
• pp.57-64
• /
• 2014

Most previous studies of software fault prediction model which determines the fault-proneness of input modules have focused on supervised learning model using training data set. However, Unsupervised learning model is needed in case supervised learning model cannot be applied: either past training data set is not present or even though there exists data set, current project type is changed. Building an unsupervised learning model is extremely difficult that is why only a few studies exist. In this paper, we build unsupervised models using representative clustering algorithms, EM and DBSCAN, that have not been used in prior studies and compare these models with the previous model using K-means algorithm. The results of our study show that the EM model performs slightly better than the K-means model in terms of error rate and these two models significantly outperform the DBSCAN model.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.3
• /
• pp.127-133
• /
• 2019

Most studies of software fault prediction have been about supervised learning models that use only labeled training data. Although supervised learning usually shows high prediction performance, most development groups do not have sufficient labeled data. Unsupervised learning models that use only unlabeled data for training are difficult to build and show poor performance. Semi-supervised learning models that use both labeled data and unlabeled data can solve these problems. Self-training technique requires the fewest assumptions and constraints among semi-supervised techniques. In this paper, we implemented several models using self-training algorithms and evaluated them using Accuracy and AUC. As a result, YATSI showed the best performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.37 no.5
• /
• pp.425-432
• /
• 2009

In this study, the ability of neural network in modeling and predicting of the unsteady aerodynamic force coefficients of 2D airfoil with the data obtained from Euler CFD code has been confirmed. Neural network models are constructed based on supervised training process using Levenberg-Marquardt algorithm, combining this into genetic algorithm, hybrid genetic algorithm and the efficiency of the two cases are analyzed and compared. It is shown that hybrid-genetic algorithm is more efficient for neural network of complex system and the predicted properties of the unsteady aerodynamic force coefficients of 2D airfoil by the neural network models are confirmed to be similar to that of the numerical results and verified as suitable representing reduced models.

• (The) Research of the performance art and culture
• /
• no.18
• /
• pp.481-512
• /
• 2009

This thesis is to investigate the effectiveness of Cinema Therapy through the aspect of vicarious learning, that is, Nayeoug's modelling after Yeonsun, and Yeonsun's modelling after The Little Mermaid, by making My Mother, the Mermaid directed by Park Heungsik. After immature Nayeoung returns from the travel into past time, she is reborn as an mature woman, and finally she can manage a happy marriage life. In Nayeoung's initiation, there is Yeonsun's initiation, in that again, there is a initiation of The Little Mermaid by Hans Christian Andersen. This work is a proper text in explaining the effectiveness of Cinema Therapy which aims at self-awareness and self-improvement because it contains some aspects of the vicarious learning through the movie. Nayeon's mother(Yeonsun), Nayeoung's father(Jinguk) have trouble, and sometimes have friendly relations. The major characters' wish and need are examined out through the analysis of the five basic needs based on reality therapy. As a result, it is found out that when their needs are fulfilled, friendly relation is formed, and when their needs are not fulfilled, unfriendly relation is formed. If their own basic desires are examined, their desires can be fulfilled through the inner control by themselves.