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Kernel Estimators of the roc curve with Censored Data

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Acta Mathematicae Applicatae Sinica 2013年第1期29卷 43-54页

作者： Fang-fang Bai Yong Zhou Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Statistics and Management Shanghai University of Finance and Economics

Receiver operating characteristic （roc） curves are often used to study the two sample problem in medical studies. However, most data in medical studies are censored. Usually a natural estimator is based on the Kaplan-Meier estimator. In this paper we propose a smoothed estimator based on kernel techniques for the roc curve with censored data. The large sample properties of the smoothed estimator are established. Moreover, deficiency is considered in order to compare the proposed smoothed estimator of the roc curve with the empirical one based on Kaplan-Meier estimator. It is shown that the smoothed estimator outperforms the direct empirical estimator based on the Kaplan-Meier estimator under the criterion of deficiency. A simulation study is also conducted and a real data is analyzed.

关键词： roc curve smoothed estimator censored data Kaplan-Meier estimator deficiency

A Novel Industrial Intrusion Detection Method based on Threshold-optimized CNN-BiLSTM-Attention using roc curve

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A Novel Industrial Intrusion Detection Method based on Thres...

A New Classifier for Imbalanced Data Based on a Generalized Density Ratio Model

第三十九届中国控制会议

作者： Mindi Lan Jun Luo Senchun Chai Ruiqi Chai Chen Zhang Baihai Zhang School of Automation Beijing Institute of Technology School of Aerospace Transport and ManufacturingCranfield University

In recent years, many researchers have proposed many intrusion detection methods to protect the industrial ***, there are two existing problems among them: one is that they only consider the overall accuracy rate（AC） while ignoring the problem of class imbalance;another one is that they have considered the problem of class imbalance, but the detection rate（DR） is low and false positive rate（FR） is high for minority classes. In order to improve AC and DR of minority classes,we propose a method called threshold-optimized CNN-BiLSTM-Attention that combines CNN-BiLSTM-Attention model, with threshold modification method based on receiver operating characteristic（roc） curve. In this method, we use CNN-BiLSTMAttention model as a classifier and modify threshold of the classifier through roc curve. To evaluate the proposed method, we have performed experiments on the standard industrial data set. And the experimental results show that the proposed method can improve AC and the DR of minority classes at low FR, which is better than other intrusion detection methods.

关键词： Industrial intrusion detection Class imbalance CNN-BiLSTM-Attention Threshold modification roc curve

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Communications in Mathematics and Statistics 2023年第2期11卷 369-401页

作者： Junjun Li Wenquan Cui Department of Statistics and Finance School of ManagementUniversity of Science and Technology of ChinaHefei 230026People’s Republic of China

Achieving higher true positive rate when decreasing false positive rate is always a great challenge to the imbalance learning *** work combines penalized empirical likelihood method,lower bound algorithm and Nyströmmethod and applies these techniques along with kernel method to density ratio *** resulting classifier,density ratio classifier(DRC),is a combination of kernelization,regularization,efficient implementation and threshold moving,all of which are critical to enable DRC to be an effective and powerful method for solving difficult imbalance *** with other methods,DRC is competitive in that it is widely applicable and it is simple and easy to use without additional imbalance handling *** addition,the convergence rate of the estimate of log density ratio is discussed as *** the results of numerical analysis also show that DRC outperforms other methods in AUC and G-mean score.

关键词： Classifier Density ratio model Imbalance problems Kernel method roc curve

BP neural networks and random forest models to detect damage by Dendrolimus punctatus Walker

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Journal of Forestry Research 2020年第1期31卷 107-121页

作者： Zhanghua Xu Xuying Huang Lu Lin Qianfeng Wang Jian Liu Kunyong Yu Chongcheng Chen College of Environment and Resources Fuzhou UniversityFuzhou 350116People’s Republic of China Fujian Provincial Key Laboratory of Resources and Environment Monitoring and Sustainable Management and Utilization Sanming 365004People’s Republic of China Key Lab of Spatial Data Mining and Information Sharing Ministry of EducationFuzhou 350116People’s Republic of China

The construction of a pest detection algorithm is an important step to couple"ground-space"characteristics,which is also the basis for rapid and accurate monitoring and detection of pest *** four experimental areas in Sanming City,Jiangle County,Sha County and Yanping District in Fujian Province,sample data on pest damage in 182 sets of Dendrolimus punctatus were *** data were randomly divided into a training set and testing set,and five duplicate tests and one eliminating-indicator test were *** on the characterization analysis of the host for *** damage,seven characteristic indicators of ground and remote sensing including leaf area index,standard error of leaf area index(SEL)of pine forest,normalized difference vegetation index(NDVI),wetness from tasseled cap transformation(WET),green band(B2),red band(B3),near-infrared band(B4)of remote sensing image are obtained to construct BP neural networks and random forest models of pest *** detection results of these two algorithms were comprehensively compared from the aspects of detection precision,kappa coefficient,receiver operating characteristic curve,and a paired t *** results showed that the seven indicators all were responsive to pest damage,and NDVI was relatively weak;the average pest damage detection precision of six tests by BP neural networks was 77.29%,the kappa coefficient was 0.6869 and after the RF algorithm,the respective values were 79.30%and 0.7151,showing that the latter is more optimized,but there was no significant difference(p>0.05);the detection precision,kappa coefficient and AUC of the RF algorithm was higher than the BP neural networks for three pest levels(no damage,moderate damage and severe damage).The detection precision and AUC of BP neural networks were a little higher for mild damage,but the difference was not significant(p>0.05)except for the kappa coefficient for the no damage level(p<0.05).An"over-fitting"phenomenon tends to occur in BP neur

关键词： BP neural networks Detection precision Kappa coefficient Pine moth Random forest roc curve

The use of evidential belief functions for mineral potential mapping in the Nanling belt, South China

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Frontiers of Earth Science 2015年第2期9卷 342-354页

作者： Yue LIU Qiuming CHENG Qinglin XIA Xinqing WANG State Key Laboratory of Geological Processes and Mineral Resources China University of Geosciences Wuhan 430074 China Faculty of Earth Resources China University of Geosciences Wuhan 430074 China Department of Earth and Space Science and Engineering Department of Geography York University Toronto M3JIP3 Canada

In this study, the evidential belief functions （EBFs） were applied for mapping tungsten polymetallic potential in the Nanling belt, South China. Seven evidential layers （e.g., geological, geochemical, and geophysical） related to tungsten polymetallic deposits were extracted from a multi-source geospatial database. The relationships between evidential layers and the target deposits were quantified using EBFs model. Four EBF maps （belief map, disbelief map, uncertainty map, and plausibility map） are generated by integrating seven evidential layers which provide meaningful interpretations for tungsten polymetallic potential. On the final predictive map, the study area was divided into three target zones of high potential, moderate potential, and low potential areas, among which high potential and moderate potential areas accounted for 17.8% of the total area, containing 81% of the total deposits. To evaluate the success rate accuracy, the receiver operating characteristic （roc） curves and the area under the curves （AUC） for the belief map were calculated. The area under the curve is 0.81 which indicates that the capability for correctly classifying the areas with existing mineral deposits is satisfactory. The results of this study indicate that the EBFs were effectively used for mapping mineral potential and for managing uncertainties asso- ciated with evidential layers.

关键词： Dempster-Shafer theory of evidence GIS,uncertainty tungsten polymetallic deposit roc curve

Biochemical and radiological predictors of malignant biliary strictures

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World Journal of Gastroenterology 2004年第10期10卷 1504-1507页

作者： Ibrahim A.AI-Mofleh Abdulrahman M.Aljebreen Saleh M.AlAmri Rashed S.AJ-Rashed Faleh Z.Al-Faleh Hussein M.AJ-Freihi Ayman A.Abdo Arthur C.Isnani Gastroenterology Division department of Medicine (38)King Khalid University HospitalRiyadhKingdom of Saudi Arabia King Khalid University Hospital College of Medicine and Research Center (74)PO Box 2925Riyadh 11461Kingdom of Saudi Arabia

AIM: Differentiation of benign biliary strictures (BBS) from malignant biliary strictures (MBS) remains difficult despite improvement in imaging and endoscopic techniques. The aim of this study was to identify the clinical, biochemical and or radiological predictors of malignant biliary ***: We retrospectively reviewed all charts of patients who had biliary strictures (BS) on endoscopic retrograde cholangiopancreatography (ERCP) or percutaneous cholangiography (PTC) in case of unsuccessful ERCP from March 1998 to August 2002. Patient characteristics, clinical features, biochemical, radiological and biopsy results were all recorded. Stricture etiology was determined based on cytology,biopsy or clinical follow-up. A receiver operator characteristic (roc) curve was constructed to determine the optimal laboratory diagnostic criterion threshold in predicting ***: One hundred twenty six patients with biliary strictures were enrolled, of which 72 were malignant. The mean age for BBS was 53 years compared to 62.4 years for MBS (P=0.0006). Distal bile duct stricture was mainly due to a malignant process 48.6% vs 9% (P=0.001). Alkaline phosphates and AST levels were more significantly elevated in MBS (P=0.0002). roc curve showed that a bilirubin level of 84 μmol/L or more was the most predictive of MBS with a sensitivity of 98.6%, specificity of 59.3% and a positive likelihood ratio of 2.42 (95% CI=0.649-0.810). Proximal biliary dilatation was more frequently encountered in MBS compared to BBS, 73.8% vs39.5% (P=0.0001). Majority of BBS (87%) and MBS (78%) were managed ***: A serum bilirubin level of 84 μmol/L or greater is the best predictor of MBS. Older age, proximal biliary dilatation, higher levels of bilirubin, alkaline phosphatase, ALT and AST are all associated with MBS. ERCP is necessary to diagnose and treat benign and malignant biliary strictures.

关键词： Biliary Tract Diseases Biliary Tract Neoplasms Constriction, Pathologic Predictive Value of Tests Age Factors Bilirubin Cholangiography Cholangiopancreatography, Endoscopic Retrograde Humans Middle Aged roc curve Retrospective Studies Sensitivity and Specificity

A semiparametric Wald statistic for testing logistic regression models based on case-control data

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Science China Mathematics 2008年第11期51卷 2020-2032页

作者： WAN ShuWen Biostatistics Lab, School of Life Sciences, Nanjing University, Nanjing 210093, China Biostatistics Lab School of Life Sciences Nanjing University Nanjing China

We propose a semiparametric Wald statistic to test the validity of logistic regression models based on case-control data. The test statistic is constructed using a semiparametric roc curve estimator and a nonparametric roc curve estimator. The statistic has an asymptotic chi-squared distribution and is an alternative to the Kolmogorov-Smirnov-type statistic proposed by Qin and Zhang in 1997, the chi-squared-type statistic proposed by Zhang in 1999 and the information matrix test statistic proposed by Zhang in 2001. The statistic is easy to compute in the sense that it requires none of the following methods: using a bootstrap method to find its critical values, partitioning the sample data or inverting a high-dimensional matrix. We present some results on simulation and on analysis of two real examples. Moreover, we discuss how to extend our statistic to a family of statistics and how to construct its Kolmogorov-Smirnov counterpart.

关键词： case-control data density ratio model empirical likelihood Kolmogorov-Smirnov statistic logistic regression roc curve 30P12 32C12

Selecting decision trees for power system security assessment

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Energy and AI 2021年第4期6卷 21-30页

作者： Al-Amin B.Bugaje Jochen L.Cremer Mingyang Sun Goran Strbac Department of Electrical&Electronic Engineering Imperial College LondonLondonSW72AZUK Department of Electrical Sustainable Energy TU DelftMekelweg 52628 CD DelftNetherlands Department of Control Science and Engineering Zhejiang UniversityHangzhou 310027China

Power systems transport an increasing amount of electricity,and in the future,involve more distributed renewables and dynamic interactions of the *** system response to disturbances must be secure and predictable to avoid power *** system response can be simulated in the time ***,this dynamic security assessment(DSA)is not computationally tractable in *** promising is to train decision trees(DTs)from machine learning as interpretable classifiers to predict whether the systemwide responses to disturbances are *** most research,selecting the best DT model focuses on predictive ***,it is insufficient to focus solely on predictive *** alarms and false alarms have drastically different costs,and as security assessment is a critical task,interpretability is crucial for *** this work,the multiple objectives of interpretability,varying costs,and accuracies are considered for DT model *** propose a rigorous workflow to select the best *** addition,we present two graphical approaches for visual inspection to illustrate the selection sensitivity to probability and impacts of *** propose cost curves to inspect selection combining all three objectives for the first *** studies on the IEEE 68 bus system and the French system show that the proposed approach allows for better DT-selections,with an 80%increase in interpretability,5%reduction in expected operating cost,while making almost zero accuracy *** proposed approach scales well with larger systems and can be used for models beyond ***,this work provides insights into criteria for model selection in a promising application for methods from artificial intelligence(AI).

关键词： Dynamic security assessment Machine learning Decision trees roc curve Cost curves Cost sensitivity

Study on the value of serum miR-106b for the early diagnosis of hepatocellular carcinoma

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World Journal of Gastroenterology 2017年第20期23卷 3713-3720页

作者： Bao-Min Shi Wen Lu Kun Ji Yu-Feng Wang Shuai Xiao Xiu-Yan Wang Department of General Surgery Tongji HospitalMedical School of Tongji University Department of Ultrasound Tongji HospitalMedical School of Tongji University

AIM To analyze the incidence of hepatocellular carcinoma (HCC) in a population that underwent health checkups and had high serum miR-106b levels. METHODS A total of 335 subjects who underwent checkups in the Digestive and Liver Disease Department of our hospital were randomly selected. RT-PCR was used to detect the level of miR-106b in serum samples. Laboratory and imaging examinations were carried out to confirm the HCC diagnosis in patients who had a > 2-fold change in miR-106b levels. Ultrasound-guided biopsy was also used for HCC diagnosis when necessary. On this basis, the clinical data of these subjects, including history of hepatitis virus infection, obesity, long-term history of alcohol use and stage of HCC, were collected. Then, the impact of these factors on the level of miR1-06b in serum was analyzed. Furthermore, receiver operating characteristic (roc) curve was drawn to evaluate the diagnostic efficacy of miR-106b for HCC. RESULTS A total of 35 subjects had abnormal serum miR-106b levels, of which 20 subjects were diagnosed with HCC. t-test revealed that the difference in serum miR-106b level in terms of sex, age, history of hepatitis virus infection, obesity and long-term history of alcohol use was not statistically significant. However, serum miR-106b levels in patients with advanced HCC (stage. /.) was higher than in patients with early HCC (stage./.), and the difference was statistically significant (P = 0.000). Moreover, the roc curve revealed that the area under the curve value for miR-106b was 0.885, which shows that serum miR-106b level has a certain clinical value for HCC diagnosis. CONCLUSION The random sampling survey shows that serum miR-106b level is a valuable diagnostic marker for HCC. However, the diagnostic threshold value needs to be further researched.

关键词： MiR-106b Hepatocellular carcinoma roc curve Random sampling survey