关键词： 联合模型   机器学习   殃残差   Cox-Snell残差  

摘要： 本文运用机器学习方法对纵向数据与生存数据建模,以机器学习方法代替纵向子模型中的线性随机效应模型;生存子模型仍运用Cox比例危险模型。与传统的建模方法做对比,此建模方法的生存子模型残差图诊断符合理论结果,纵向子模型的残差要比线性混合模型分散。

关键词： 大数据   频谱大数据   机器学习   数据挖掘   无线通信   物联网  

摘要： 随着移动互联网与物联网的迅猛发展,个人无线设备的数量呈现指数级增长,随之产生的海量频谱数据与日俱增,频谱大数据的存在已成事实。同时,频谱赤字也日益严峻。为提高频谱利用率,有效的频谱大数据处理显得十分重要。本文从无线通信的角度,首先给出了频谱大数据的定义并分析了它的基本特征;然后总结了一些对于频谱大数据分析与利用颇具前景的机器学习方法,如分布式和并行式学习、极速学习、核学习、深度学习、强化学习、博弈学习和迁移学习;最后给出了几个开放性话题和研究趋势。

关键词： 在线学习   机器学习   故障预警  

摘要： 通信设备故障预警技术已经不能满足针对通信网络的故障管理需求,以往通过规则库或专家系统实现故障预警系统时规则库或经验很难定义描述,本文在充分研究在线机器学习方法的基础上,提出了基于在线学习算法的通信设备故障预警技术,核心在于针对训练样本进行故障特征提取、训练分类器,然后用训练好的分类器去实时监测故障。

关键词： 计算机网络结构   网络结构优化   遗传算法   优化理论   机器学习方法   梯度下降算法   优化问题   迭代计算  

关键词： CLOUD-TOP PROPERTIES   NOWCASTING SYSTEM   STORM INITIATION   PART II   CLASSIFICATION   RAINFALL   PRECIPITATION   CLIMATOLOGY   TEMPERATURE   EVOLUTION  

摘要： As convective clouds in Northeast Asia are accompanied by various hazards related with heavy rainfall and thunderstorms, it is very important to detect convective initiation (CI) in the region in order to mitigate damage by such hazards. In this study, a novel approach for CI detection using images from Meteorological Imager (MI), a payload of the Communication, Ocean, and Meteorological Satellite (COMS), was developed by improving the criteria of the interest fields of Rapidly Developing Cumulus Areas (RDCA) derivation algorithm, an official CI detection algorithm for Multi-functional Transport SATellite-2 (MTSAT-2), based on three machine learning approaches-decision trees (DT), random forest (RF), and support vector machines (SVM). CI was defined as clouds within a 16 x 16 km window with the first detection of lightning occurrence at the center. A total of nine interest fields derived from visible, water vapor, and two thermal infrared images of MI obtained 15-75 min before the lightning occurrence were used as input variables for CI detection. RF produced slightly higher performance (probability of detection (POD) of 75.5% and false alarm rate (FAR) of 46.2%) than DT (POD of 70.7% and FAR of 46.6%) for detection of CI caused by migrating frontal cyclones and unstable atmosphere. SVM resulted in relatively poor performance with very high FAR ~83.3%. The averaged lead times of CI detection based on the DT and RF models were 36.8 and 37.7 min, respectively. This implies that CI over Northeast Asia can be forecasted ~30-45 min in advance using COMS MI data.

关键词： INTERACTION NETWORKS   FEATURE-SELECTION   INFORMATION  

摘要： Motivation: Anatomical Therapeutic Chemical (ATC) classification system, widely applied in almost all drug utilization studies, is currently the most widely recognized classification system for drugs. Currently, new drug entries are added into the system only on users' requests, which leads to seriously incomplete drug coverage of the system, and bioinformatics prediction is helpful during this process. Results: Here we propose a novel prediction model of drug-ATC code associations, using logistic regression to integrate multiple heterogeneous data sources including chemical structures, target proteins, gene expression, side-effects and chemical-chemical associations. The model obtains good performance for the prediction not only on ATC codes of unclassified drugs but also on new ATC codes of classified drugs assessed by cross-validation and independent test sets, and its efficacy exceeds previous methods. Further to facilitate the use, the model is developed into a user-friendly web service SPACE (Similarity-based Predictor of ATC CodE), which for each submitted compound, will give candidate ATC codes (ranked according to the decreasing probability_score predicted by the model) together with corresponding supporting evidence. This work not only contributes to knowing drugs' therapeutic, pharmacological and chemical properties, but also provides clues for drug repositioning and side-effect discovery. In addition, the construction of the prediction model also provides a general framework for similarity-based data integration which is suitable for other drug-related studies such as target, side-effect prediction etc.

关键词： NLP   k-means   clustering   用户反馈   单词云  

摘要： 了解用户反馈信息对于改进购物网站的服务质量非常重要,但工作量很大。通过机器学习与自然语言处理的方法,可以将用户评论进行聚类,并构造一种可视化界面工具,有助于网站分析师与项目经理提升工作效率,简化工作流程。基于此,将对聚类算法,自然语言处理过程以及用户反馈信息处理工具中的一些重要功能进行介绍。

关键词： 异音检测   支持向量机   电机故障  

摘要： 在大批量小型电机生产线上,普遍采用的听音质检工序需要大量训练有素的工人。针对电机质检工序声音信号的统计特征及质检工艺的特点,提出基于一类学习的异响检测的方法。该方法以正常样本为基础建立质检判别函数,避免了其他分类算法要求训练样本类别全面和覆盖广泛的条件。给出了该方法的实现过程,并通过大量实测样本验证了该方法的有效性。

关键词： 机器博弈   机器学习   智能  

摘要： 该文介绍了机器博弈技术,给出了提升计算机的智能程度是研究机器博弈技术的重点。设计了五子棋游戏算法,由于算法设计决定了计算机的智能程度,该算法没有用到机器学习,计算机不具有智能。分析了卡斯帕罗夫和＂深蓝＂的不同特点,给出了＂深蓝＂战胜世界冠军的启示,只有利用机器学习技术开发的具备学习能力的计算机才具有智能。