基于各类支持度阈值独立挖掘的关联改进算法

关联分类及较多的改进算法很难同时既具有较高的整体准确率又有较好的小类分类性能。针对此问题,提出了一种基于类支持度阈值独立挖掘的关联分类改进算法—ACCS。ACCS算法的主要特点是:(1)根据训练集中各类数量大小给出每个类类支持度阈值的设定方法,并基于各类的类支持度阈值独立挖掘该类的关联分类规则,尽量使小类生成更多高置信度的规则;(2)采用类支持度对置信度相同的规则排序,提高小类规则的优先级;(3)用综合考虑置信度和提升度的新的规则度量预测未知实例。在多个数据集上的实验结果表明,相比多种关联分类改进算法,ACCS算法有更高的整体分类准确率,且在不平衡数据上也能取得较好的小类分类性能。     

基于支持度和增比率的改进关联分类算法

关联分类是一项重要的分类技术,目前普遍采用基于支持度和置信度的关联分类模式。但是,用支持度度量项集的分类能力过于简单,且置信度不能度量项集与类的相关性,所以利用支持度和置信度容易产生质量不好的规则。提出改进的关联分类算法—ACSER。ACSER不仅考虑项集到本类的支持度,也考虑项集到补类的支持度。首先,提取频繁增比模式作为分类候选规则集;其次,利用置信度和增比率度量规则的强度,按照其强度进行排序和剪枝;最后,选择k条最优的规则进行预测。在16个UCI数据集上的实验结果表明,改进的分类算法ACSER与传统的分类算法相比有更高的分类准确率。     

一种改进的关联分类算法

基于支持度-置信度的关联分类是一项重要的分类算法,这种关联分类算法先构建频繁项集,然后通过置信度的阈值来选取规则,容易产生质量不高的规则。针对这个问题,提出了一种改进关联分类算法:首先,选取大量的属性值对建立起条件小训练集;其次,每条规则主体通过选取条件小训练集中最好属性值对连接生成;最后,采用实例覆盖技术覆盖小训练集的每个实例,构建具有较高质量的分类器。在25个UCI数据集上的实验结果表明,所提出的改进关联分类算法的准确率得到了显著提高。     

使用多支持度的关联规则分类算法

传统关联分类算法使用单一最小项目支持度挖掘关联规则,导致稀有项关联规则无法被发现,从而影响分类的准确性和实用性。提出一种多支持度关联规则分类算法MS-CBAR(Multiple Supports-Classification Based on Association Rules),将多最小项目支持度模型应用于关联分类,以有效挖掘稀有项。该算法为数据库中的规则项提供了用户可定义的最小项目支持度。MS-CBAR算法使用项的最小项支持度阈值、类的最小类支持度值和规则项的最小支持度值决定分类规则是否频繁。生成分类规则集后,使用最高优先度规则覆盖法基于规则集建立分类器。实验表明,所提算法在包含稀有项目及稀有类的数据集中准确率高于传统关联分类算法及其相关算法,表现更稳定。     

基于支持度与置信度阈值优化技术的关联分类算法

基于关联规则的分类算法中，支持度和置信度阈值的设置会影响分类器的准确率。以往的关联分类算法都根据经验人为地设置支持度和置信度的阈值，很难保证分类器总能达到较好的分类效果。为了解决该问题，可以将优化求解策略引入到关联分类过程中。通过利用爬山法搜索技术来获得使分类准确率最高的支持度与置信度阈值，对Apriori_TFP_CMAR关联分类算法进行改进，避免了阈值设置不合理影响最终分类效果的问题，提高了关联分类算法的分类准确率。     

基于信息增益的中文文本关联分类

关联分类是一种通过挖掘训练集中的关联规则,并利用这些规则预测新数据类属性的分类技术。最近的研究表明,关联分类取得了比传统的分类方法如C4.5更高的准确率。现有的基于支持度-置信度架构的关联分类方法仅仅是选择频繁文字构建分类规则,忽略了文字的分类有效性。本文提出一种新的ACIG算法,结合信息增益与FoilGain在中文文本中选择规则的文字,以提高文字的分类有效性。实验结果表明,ACIG算法比其他关联分类算法(CPAR)有更高的准确率。     

基于排序的关联分类算法

提出了一种基于排序的关联分类算法.利用基于规则的分类方法中择优方法偏爱高精度规则的思想和考虑尽可能多的规则,改进了CBA(Classification Based on Associations)只根据少数几条覆盖训练集的规则构造分类器的片面性.首先采用关联规则挖掘算法产生后件为类标号的关联规则,然后根据长度、置信度、支持度和提升度等对规则进行排序,并在排序时删除对分类结果没有影响的规则.排序后的规则加上一个默认分类便构成最终的分类器.选用20个UCI公共数据集的实验结果表明,提出的算法比CBA具有更高的平均分类精度.     

基于选择度的分类规则学习算法

规则式分类器通常使用单一度量选择属性值,然而单一度量会导致很多属性值具有相同的度量值,从而无法选择出"好"的属性值。此外,规则式分类器通常提取置信度为100%的规则,致使规则提取过程比较费时,并且所得到的规则支持度较低。针对上述不足,提出新的属性值度量——选择度。选择度是基于信息熵、类支持度及偏离度3种度量的结合,能更好地区分属性值的优劣。在此基础上,提出一种基于选择度的分类规则学习算法LRSM。在LRSM算法中,当规则包含的负实例数小于给定域值时,该规则被抽取,删除被此规则覆盖的实例,抽取下一条规则。实验结果表明,与FOIL算法相比较,LRSM算法提高了分类准确率,同时明显地减少了分类所消耗的时间。     

基于属性重要性的关联分类方法

提出了基于属性重要性的关联分类方法.与传统算法不同的是根据属性重要性程度生成类别关联规则;并且在构造分类器时改进了CBA算法中对于具有相同支持度、置信度规则选择时的随机性.实验结果证明,用该方法得到的分类规则与传统的关联分类算法相比,复杂度低,且有效提高了分类效果.     

一种面向不平衡数据分类的组合剪枝方法

传统的数据分类算法多是基于平衡的数据集创建,对不平衡数据分类时性能下降,而实践表明组合选择能有效提高算法在不平衡数据集上的分类性能。为此,从组合选择的角度考虑不平衡类学习问题,提出一种新的组合剪枝方法,用于提升组合分类器在不平衡数据上的分类性能。使用Bagging建立分类器库,直接用正类(少数类)实例作为剪枝集,并通过MBM指标和剪枝集,从分类器库中选择一个最优或次优子组合分类器作为目标分类器,用于预测待分类实例。在12个UCI数据集上的实验结果表明,与EasyEnsemble、Bagging和C4.5算法相比,该方法不但能大幅提升组合分类器在正类上的召回率,而且还能提升总体准确率。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

基于QTE的蒙古文显示机制研究与实现

蒙古语言是中国蒙古族使用的通用语言,由于蒙古文区别于其他文字的书写方式和其自身变形机制等特点,在很多通用的文字处理引擎中都不被支持。在嵌入式产品开发与应用领域中Linux加QTE已经成为流行方式。该文给出了一种在QTE环境上实现基于标准Unicode的蒙古文点阵显示和变形算法, 并自定义了支持蒙古文的QTE组件,扩展了QTE功能,为在Linux加QTE方式的嵌入式体系结构中处理蒙古文提供了一种解决方法。