Log. J. IGPL最新文献_第9页

Missing data imputation over academic records of electrical engineering students 电气工程专业学生学业成绩数据缺失

Log. J. IGPL Pub Date : 2019-12-13 DOI: 10.1093/jigpal/jzz056

Esteban Jove, P. Blanco-Rodríguez, J. Casteleiro-Roca, Héctor Quintián-Pardo, Francisco Javier Moreno Arboleda, J. López-Vázquez, B. A. Rodríguez-Gómez, M. Meizoso-López, A. P. Pazos, F. J. D. C. Juez, Sung-Bae Cho, J. Calvo-Rolle

{"title":"Missing data imputation over academic records of electrical engineering students","authors":"Esteban Jove, P. Blanco-Rodríguez, J. Casteleiro-Roca, Héctor Quintián-Pardo, Francisco Javier Moreno Arboleda, J. López-Vázquez, B. A. Rodríguez-Gómez, M. Meizoso-López, A. P. Pazos, F. J. D. C. Juez, Sung-Bae Cho, J. Calvo-Rolle","doi":"10.1093/jigpal/jzz056","DOIUrl":"https://doi.org/10.1093/jigpal/jzz056","url":null,"abstract":"\u0000 Nowadays, the quality standards of higher education institutions pay special attention to the performance and evaluation of the students. Then, having a complete academic record of each student, such as number of attempts, average grade and so on, plays a key role. In this context, the existence of missing data, which can happen for different reasons, leads to affect adversely interesting future analysis. Therefore, the use of imputation techniques is presented as a helpful tool to estimate the value of missing data. This work deals with the academic records of engineering students, in which imputation techniques are applied. More specifically, it is assessed and compared to the performance of the multivariate imputation by chained equations methodology, the adaptive assignation algorithm (AAA) based on multivariate adaptive regression splines and a hybridization based on self-organisation maps with Mahalanobis distances and AAA algorithm. The results show that proposed methods obtain successfully results regardless the number of missing values, in general terms.","PeriodicalId":304915,"journal":{"name":"Log. J. IGPL","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126847405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Knowledge in action: logico-philosophical approach to linguistic evidentiality 行动中的知识:语言证据的逻辑哲学方法

Log. J. IGPL Pub Date : 2019-12-13 DOI: 10.1093/jigpal/jzz040

Cristina Barés Gómez, M. Fontaine, A. Nepomuceno

引用次数: 3

Non-removal strategy for outliers in predictive models: The PAELLA algorithm case 预测模型中异常值的非去除策略:PAELLA算法案例

Log. J. IGPL Pub Date : 2019-12-09 DOI: 10.1093/jigpal/jzz052

M. C. Limas, H. Alaiz-Moretón, Laura Fernández-Robles, Javier Alfonso-Cendón, C. F. Llamas, Lidia Sánchez-González, H. Pérez

{"title":"Non-removal strategy for outliers in predictive models: The PAELLA algorithm case","authors":"M. C. Limas, H. Alaiz-Moretón, Laura Fernández-Robles, Javier Alfonso-Cendón, C. F. Llamas, Lidia Sánchez-González, H. Pérez","doi":"10.1093/jigpal/jzz052","DOIUrl":"https://doi.org/10.1093/jigpal/jzz052","url":null,"abstract":"\u0000 This paper reports the experience of using the PAELLA algorithm as a helper tool in robust regression instead of as originally intended for outlier identification and removal. This novel usage of the algorithm takes advantage of the occurrence vector calculated by the algorithm in order to strengthen the effect of the more reliable samples and lessen the impact of those that otherwise would be considered outliers. Following that aim, a series of experiments is conducted in order to learn how to better use the information contained in the occurrence vector. Using a contrively difficult artificial data set, a reference predictive model is fit using the whole raw dataset. The second experiment reports the results of fitting a similar predictive model but discarding the samples marked as outliers by PAELLA. The third experiment uses the occurrence vector provided by PAELLA in order to classify the observations in multiple bins and fit every possible model changing which bins are considered for fitting and which are discarded in that particular model. The fourth experiment introduces a sampling process before fitting in which the occurrence vector represents the likelihood of being considered in the training data set. The fifth experiment considers the sampling process as an internal step to be performed interleaved between the training epochs. The last experiment compares our approach using weighted neural networks to a state of the art method.","PeriodicalId":304915,"journal":{"name":"Log. J. IGPL","volume":"304 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134272640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Self-Organizing Maps to Validate Anti-Pollution Policies 自组织地图以验证反污染政策

Log. J. IGPL Pub Date : 2019-12-09 DOI: 10.1093/jigpal/jzz049

Ángel Arroyo, Carlos Cambra, Álvaro Herrero, V. Tricio, E. Corchado

引用次数: 0

Evolutionary Reinforcement Learning for Adaptively Detecting Database Intrusions 进化强化学习自适应检测数据库入侵

Log. J. IGPL Pub Date : 2019-12-09 DOI: 10.1093/jigpal/jzz053

Seul-Gi Choi, Sung-Bae Cho

{"title":"Evolutionary Reinforcement Learning for Adaptively Detecting Database Intrusions","authors":"Seul-Gi Choi, Sung-Bae Cho","doi":"10.1093/jigpal/jzz053","DOIUrl":"https://doi.org/10.1093/jigpal/jzz053","url":null,"abstract":"\u0000 Relational database management system (RDBMS) is the most popular database system. It is important to maintain data security from information leakage and data corruption. RDBMS can be attacked by an outsider or an insider. It is difficult to detect an insider attack because its patterns are constantly changing and evolving. In this paper, we propose an adaptive database intrusion detection system that can be resistant to potential insider misuse using evolutionary reinforcement learning, which combines reinforcement learning and evolutionary learning. The model consists of two neural networks, an evaluation network and an action network. The action network detects the intrusion, and the evaluation network provides feedback to the detection of the action network. Evolutionary learning is effective for dynamic patterns and atypical patterns, and reinforcement learning enables online learning. Experimental results show that the performance for detecting abnormal queries improves as the proposed model learns the intrusion adaptively using Transaction Processing performance Council-E scenario-based virtual query data. The proposed method achieves the highest performance at 94.86%, and we demonstrate the usefulness of the proposed method by performing 5-fold cross-validation.","PeriodicalId":304915,"journal":{"name":"Log. J. IGPL","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128952252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On Fingerprinting of Public Malware Analysis Services 公共恶意软件分析服务的指纹识别研究

Log. J. IGPL Pub Date : 2019-12-07 DOI: 10.1093/jigpal/jzz050

Alvaro Botas, R. Rodríguez, Vicente Matellán Olivera, Juan Felipe García Sierra, M. T. Trobajo, M. Carriegos

引用次数: 1

Pragmatic logics for hypotheses and evidence 假设和证据的实用逻辑

Log. J. IGPL Pub Date : 2019-12-05 DOI: 10.1093/jigpal/jzz042

Massimiliano Carrara, D. Chiffi, C. Florio

引用次数: 1

Corrigendum: The Keisler - Shelah theorem for QmbC through semantical atomization 更正:通过语义原子化的QmbC的Keisler - Shelah定理

Log. J. IGPL Pub Date : 2019-11-25 DOI: 10.1093/JIGPAL/JZZ024

T. M. Ferguson