Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications最新文献_第3页

A Memory-Enhanced Framework for Financial Fraud Detection 金融欺诈检测的记忆增强框架

Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications Pub Date : 2018-01-01 DOI: 10.1109/ICMLA.2018.00140

Kunlin Yang

引用次数: 0

AUTOMATIC SCORING OF A NONWORD REPETITION TEST. 非单词重复测试的自动评分。

Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications Pub Date : 2017-12-01 Epub Date: 2018-01-18 DOI: 10.1109/icmla.2017.0-143

Meysam Asgari, Jan Van Santen, Katina Papadakis

引用次数: 0

Metabolic Profiling of 1H NMR Spectra in Chronic Kidney Disease with Local Predictive Modeling 用局部预测模型分析慢性肾脏疾病的1H NMR代谢谱

Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications Pub Date : 2015-12-01 DOI: 10.1109/ICMLA.2015.155

M. Luck, A. Yartseva, G. Bertho, E. Thervet, P. Beaune, N. Pallet, C. Damon

{"title":"Metabolic Profiling of 1H NMR Spectra in Chronic Kidney Disease with Local Predictive Modeling","authors":"M. Luck, A. Yartseva, G. Bertho, E. Thervet, P. Beaune, N. Pallet, C. Damon","doi":"10.1109/ICMLA.2015.155","DOIUrl":"https://doi.org/10.1109/ICMLA.2015.155","url":null,"abstract":"Metabolic profiling, the study of changes in the concentration of the metabolites in the organism induced by biological differences within subpopulations, has to deal with a very large amount of complex data. It therefore requires the use of powerful data processing and machine learning methods. To overcome over-fitting, a common concern in metabolic profiling where the number of features is often much larger than the number of observations, many predictive analyses combined dimension reduction techniques with multivariate predictive linear modeling. Moreover, they built a global model that identifies biomarkers predictive of the output of interest giving their overall trend variations. However, this fails to capture local biological phenomena underlying subgroups of subjects. More recently, local exploration methods based on decision trees approaches have been applied in metabolomics but they only explore random parts of the feature space. In this study, we used a supervised rule-mining algorithm that locally and exhaustively explores the feature space to predict chronic kidney disease (CDK) stages based on proton Nuclear Magnetic Resonance (1H NMR) data. From the discriminant subregions obtained with this exploration, we extracted local features and learned a L2-regularized Logistic regression (L2LR) classifier. We compared the resulting local predictive model with a standard one, combining classical univariate supervised feature selection techniques with a L2LR, and a model mixing both global and local features. Results show that the local predictive model is more powerful in terms of predictive performance than the mixed and global models. Additionally, it gives key insights into biological variations specific to subgroups of subjects.","PeriodicalId":74528,"journal":{"name":"Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications","volume":"1 1","pages":"176-181"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87707545","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: 6

ExpertBayes: Automatically refining manually built Bayesian networks. ExpertBayes:自动精炼人工构建的贝叶斯网络。

Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications Pub Date : 2014-12-01 DOI: 10.1109/ICMLA.2014.64

Ezilda Almeida, Pedro Ferreira, Tiago Vinhoza, Inês Dutra, Jingwei Li, Yirong Wu, Elizabeth Burnside

引用次数: 8

Phrase Based Topic Modeling for Semantic Information Processing in Biomedicine. 基于短语的生物医学语义信息处理主题建模。

Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications Pub Date : 2013-12-01 Epub Date: 2014-04-10 DOI: 10.1109/ICMLA.2013.89

Zhiguo Yu, Todd R Johnson, Ramakanth Kavuluru

{"title":"Phrase Based Topic Modeling for Semantic Information Processing in Biomedicine.","authors":"Zhiguo Yu, Todd R Johnson, Ramakanth Kavuluru","doi":"10.1109/ICMLA.2013.89","DOIUrl":"https://doi.org/10.1109/ICMLA.2013.89","url":null,"abstract":"Given that unstructured data is increasing exponentially everyday, extracting and understanding the information, themes, and relationships from large collections of documents is increasingly important to researchers in many disciplines including biomedicine. Latent Dirichlet Allocation (LDA) is an unsupervised topic modeling technique based on the \"bag-of-words\" assumption that has been applied extensively to unveil hidden semantic themes within large sets of textual documents. Recently, it was extended using the \"bag-of-n-grams\" paradigm to account for word order. In this paper, we present an alternative phrase based LDA model to move from a bag of words or n-grams paradigm to a \"bag-of-key-phrases\" setting by applying a key phrase extraction technique, the C-value method, to further explore latent themes. We evaluate our approach by using a phrase intrusion user study and demonstrate that our model can help LDA generate better and more interpretable topics than those generated using the bag-of-n-grams approach. Given topic models essentially are statistical tools, an important problem in topic modeling is that of visualizing and interacting with the models to understand and extract new information from a collection. To evaluate our phrase based modeling approach in this context, we incorporate it in an open source interactive topic browser. Qualitative evaluations of this browser with biomedical experts demonstrate that our approach can aid biomedical researchers gain better and faster understanding of their document collections.","PeriodicalId":74528,"journal":{"name":"Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications","volume":"2013 ","pages":"440-445"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ICMLA.2013.89","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35192144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Face Recognition Challenge: Object Recognition Approaches for Human/Avatar Classification 人脸识别挑战:人类/化身分类的对象识别方法

Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications Pub Date : 2012-12-12 DOI: 10.1109/ICMLA.2012.188

T. Yamasaki, Tsuhan Chen

引用次数: 5

Combining Gene Expression Profiles and Protein-Protein Interactions for Identifying Functional Modules 结合基因表达谱和蛋白质相互作用鉴定功能模块

Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications Pub Date : 2012-12-12 DOI: 10.1109/ICMLA.2012.28

Dingding Wang, M. Ogihara, Erliang Zeng, Tao Li

引用次数: 3

Feature Extraction and Selection in Ground Penetrating Radar with Experimental Data Set of Inclusions in Concrete Blocks 基于混凝土块体夹杂物实验数据集的探地雷达特征提取与选择

Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications Pub Date : 2012-12-12 DOI: 10.1109/ICMLA.2012.139

F. Queiroz, D. Vieira, X. L. Travassos, M. F. Pantoja

引用次数: 3

Clinical report classification using Natural Language Processing and Topic Modeling. 使用自然语言处理和主题建模的临床报告分类。

Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications Pub Date : 2012-12-01 Epub Date: 2013-01-10 DOI: 10.1109/icmla.2012.173

Efsun Sarioglu, Hyeong-Ah Choi, Kabir Yadav

{"title":"Clinical report classification using Natural Language Processing and Topic Modeling.","authors":"Efsun Sarioglu, Hyeong-Ah Choi, Kabir Yadav","doi":"10.1109/icmla.2012.173","DOIUrl":"https://doi.org/10.1109/icmla.2012.173","url":null,"abstract":"Large amount of electronic clinical data encompasses important information in free text format. To be able to help guide medical decision-making, text needs to be efficiently processed and coded. In this research, we investigate techniques to improve classification of Emergency Department computed tomography (CT) reports. The proposed system uses Natural Language Processing (NLP) to generate structured output from the reports and then machine learning techniques to code for the presence of clinically important injuries for traumatic orbital fracture victims. Topic modeling of the corpora is also utilized as an alternative representation of the patient reports. Our results show that both NLP and topic modeling improves raw text classification results. Within NLP features, filtering the codes using modifiers produces the best performance. Topic modeling shows mixed results. Topic vectors provide good dimensionality reduction and get comparable classification results as with NLP features. However, binary topic classification fails to improve upon raw text classification.","PeriodicalId":74528,"journal":{"name":"Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications","volume":"2012 ","pages":"204-209"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/icmla.2012.173","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41175135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 20

Improving a Gold Standard: Treating Human Relevance Judgments of MEDLINE Document Pairs. 改进金标准:处理MEDLINE文档对的人类相关性判断。

Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications Pub Date : 2011-02-04 DOI: 10.1109/ICMLA.2010.79

Won Kim, W John Wilbur

{"title":"Improving a Gold Standard: Treating Human Relevance Judgments of MEDLINE Document Pairs.","authors":"Won Kim, W John Wilbur","doi":"10.1109/ICMLA.2010.79","DOIUrl":"https://doi.org/10.1109/ICMLA.2010.79","url":null,"abstract":"Given prior human judgments of the condition of an object it is possible to use these judgments to make a maximal likelihood estimate of what future human judgments of the condition of that object will be. However, if one has a reasonably large collection of similar objects and the prior human judgments of a number of judges regarding the condition of each object in the collection, then it is possible to make predictions of future human judgments for the whole collection that are superior to the simple maximal likelihood estimate for each object in isolation. This is possible because the multiple judgments over the collection allow an analysis to determine the relative value of a judge as compared with the other judges in the group and this value can be used to augment or diminish a particular judge's influence in predicting future judgments. Here we study and compare five different methods for making such improved predictions and show that each is superior to simple maximal likelihood estimates.","PeriodicalId":74528,"journal":{"name":"Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications","volume":"2010 ","pages":"491-498"},"PeriodicalIF":0.0,"publicationDate":"2011-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ICMLA.2010.79","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29861442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2