自动替代虚假点数据的数据处理方法

本文给出自动剔除虚假点并使用合理值加以替代的方法。     

Handling selection bias when choosing actions in retail credit applications

In many situations one needs to know which action one should take with a customer to yield the greatest response. Typically, estimates of the response functions of different actions will be based on the responses of customers previously assigned to each action. Often, however, the previous assignments will not have been random, so that estimates of the response functions will be biased. We examine the case of two possible actions. We look at the error arising from using the simple OLS estimate ignoring the selection bias, and also explore the possibility of using the Heckman model to allow for the sample selectivity. The performance of Heckman’s model is then compared with the simple OLS through simulation.     

非圆截面环流器硬X射线辐射强度的绝对测量

本文给出了逃逸电子在孔拦上轰击出的硬X射线能谱及其辐射强度,描述了硬X射线闪烁谱还原成能谱的分析处理法,并对NaI(T1)探测器的绝对光峰效率进行了测量。     

Reject inference,augmentation, and sample selection

Many researchers see the need for reject inference in credit scoring models to come from a sample selection problem whereby a missing variable results in omitted variable bias. Alternatively, practitioners often see the problem as one of missing data where the relationship in the new model is biased because the behaviour of the omitted cases differs from that of those who make up the sample for a new model. To attempt to correct for this, differential weights are applied to the new cases. The aim of this paper is to see if the use of both a Heckman style sample selection model and the use of sampling weights, together, will improve predictive performance compared with either technique used alone. This paper will use a sample of applicants in which virtually every applicant was accepted. This allows us to compare the actual performance of each model with the performance of models which are based only on accepted cases.     

Classification from microarray data using probabilistic discriminant partial least squares with reject option

Microarrays are used to simultaneously determine the expressions of thousands of genes. An important application of microarrays is in the classification of samples into classes of interest (e.g. either healthy cells or tumour cells). Discriminant partial least squares (DPLS) has often been used for this purpose. In this paper, we describe an improvement to DPLS that uses kernel-based probability density functions and the Bayes rule to classify samples whilst keeping the option of not classifying the sample if this cannot be done with sufficient confidence. With this approach, those samples outside the boundaries of the known classes or from the ambiguity region between classes are rejected and only samples with a high probability of being correctly classified are indeed classified. The optimal model is found by simultaneously minimizing the misclassification and rejection costs. The method (p-DPLS with reject option) was tested with two datasets. For the human cancers dataset the accuracy (obtained by leave-one-out cross-validation) was improved from 97% to 99% when compared to p-DPLS without reject option. For the breast cancer dataset, p-DPLS with reject option was able to reject 100% of the test samples that did not belong to any of the modelled classes. These samples would have been misclassified if the reject option had not been considered.     

贴片机抛料原因分析及处理

SMT生产线要达到最大的产量和良好的产品质量,SMT生产线设备必须得到良好的维护和维修。贴片机是SMT生产线中的关键设备,抛料又是贴片机常见的故障现象,处理好贴片机抛料问题,即提高了贴片机贴装率,降低了贴片机的抛料率,且对降低生产成本和提高产品质量具有十分重要的作用。以西门子贴片机(机器型号:HS50、80S20和80F4)为例,介绍了贴片机抛料的成因和解决办法。     

基于ROC的三元再编码研究

针对三元编码矩阵中基分类器不包含被忽略样本类别先验知识的问题,该文提出一种基于接收机工作特性(ROC)曲线的矩阵再编码方法。首先基于ROC曲线寻找构造拒绝域的阈值对,从而获得最优分类器;然后利用最优分类器对训练样本中被忽略的类别进行分类,将经典的二值输出变为三值输出,从而对初始编码矩阵的码元0进行重新编码。在解码阶段,采用经典的汉明距离解码方法对未知样本进行决策。该方法能够避免基分类器的二次训练,适用于任意的三元纠错输出编码,具有良好的普适性和实用性。基于人工和UCI公共数据集的实验结果表明该方法简单高效,在不增加训练时间的基础上,能够提高解码的速度和精度,促进分类效果的提升。     

Fast and robust object tracking via Accept–Reject color histogram-based method

We present a new framework for real-time tracking method of complex non-rigid objects. This new method successfully coped with camera motion, partial occlusions, and target scale variations. The shape of the object tracker is approximated by an ellipse and its appearance by histogram based features derived from local image properties. We use an efficient search scheme (Accept–Reject color histogram-based method (AR), using Bhattacharyya kernel as a similarity measure) to find the image region with a histogram most similar to the target of object tracker. In this paper, we address the problem of scale/shape adaptation and orientation changes of the target. The proposed approach is compared with recent state-of-the-art algorithms. Extensive experiments are performed to testify the proposed method and validate its robustness and effectiveness to track the scale and orientation changes of the target in real-time.