標(biāo)題: Titlebook: Learning from Imbalanced Data Sets; Alberto Fernández,Salvador García,Francisco Herrer Book 2018 Springer Nature Switzerland AG 2018 Machi [打印本頁(yè)] 作者: Autopsy 時(shí)間: 2025-3-21 19:39
書目名稱Learning from Imbalanced Data Sets影響因子(影響力)
書目名稱Learning from Imbalanced Data Sets影響因子(影響力)學(xué)科排名
書目名稱Learning from Imbalanced Data Sets網(wǎng)絡(luò)公開度
書目名稱Learning from Imbalanced Data Sets網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Learning from Imbalanced Data Sets被引頻次
書目名稱Learning from Imbalanced Data Sets被引頻次學(xué)科排名
書目名稱Learning from Imbalanced Data Sets年度引用
書目名稱Learning from Imbalanced Data Sets年度引用學(xué)科排名
書目名稱Learning from Imbalanced Data Sets讀者反饋
書目名稱Learning from Imbalanced Data Sets讀者反饋學(xué)科排名
作者: 召集 時(shí)間: 2025-3-21 22:50 作者: Inexorable 時(shí)間: 2025-3-22 03:30
Alberto Fernández,Salvador García,Francisco HerrerOffers a comprehensive review of imbalanced learning widely used worldwide in many real applications, such as fraud detection, disease diagnosis, etc.Provides the user with the required background and作者: 套索 時(shí)間: 2025-3-22 04:47 作者: 反饋 時(shí)間: 2025-3-22 11:44
Book 2018s main features, and the most relevant proposed solutions. Additionally, it considers?the different scenarios in Data Science for which the imbalanced classification can?create a real challenge.?.This book stresses the gap with standard classification tasks by reviewing the case?studies and ad-hoc p作者: indemnify 時(shí)間: 2025-3-22 16:17
osis, etc.Provides the user with the required background and.This? book provides a general and comprehensible?overview of?? imbalanced learning.? It contains a formal description of a problem, and focuses on its main features, and the most relevant proposed solutions. Additionally, it considers?the 作者: 非實(shí)體 時(shí)間: 2025-3-22 18:15
Performance Measures,llows: First, Sect. 3.1 sets the background on the evaluation procedure. Then, Sect. 3.2 presents performance measures for crisp, nominal predictions. Section 3.3 discuss evaluation methods for scoring classifiers. Finally, Sect. 3.4 discuss probabilistic evaluation, and Sect. 3.5 concludes the chapter.作者: 諂媚于性 時(shí)間: 2025-3-22 22:33
Foundations on Imbalanced Classification,veral test beds where algorithms designed to address imbalanced classification problems can be compared. Some of these case studies will be considered in the remaining of this Book in order to analyze the behavior of the different methods discussed.作者: EXTOL 時(shí)間: 2025-3-23 03:10
Non-classical Imbalanced Classification Problems, 12.4 the problem of class imbalance when labels are associated to bags of instances, rather than individually (Multi-instance Learning), is analyzed. Next, Sect. 12.5 refers to the problem of class imbalance when there exists an ordinal relation among classes (Ordinal Classification). Finally, in Sect. 12.6 some concluding remarks are presented.作者: Expostulate 時(shí)間: 2025-3-23 05:40
Introduction to KDD and Data Science,sing the development of multiple software solutions for the treatment of data and integrating lots of Data Science algorithms. In order to better understand the nature of Data Science, this chapter is organized as follows. Sections 1.2 and 1.3 defines the Data Science terms and its workflow. Then, i作者: 招惹 時(shí)間: 2025-3-23 12:41
Cost-Sensitive Learning,orithms. The important issue of how to obtain the cost matrix is discussed in Sect. 4.2. Section 4.3 describes MetaCost, a popular wrapper approach for adapting any classifier to a cost-sensitive setting, while Sect. 4.4 discusses various aspects of cost-sensitive decision trees. Other cost-sensitiv作者: etidronate 時(shí)間: 2025-3-23 14:46 作者: 浸軟 時(shí)間: 2025-3-23 21:16
Algorithm-Level Approaches,given to four groups of methods. First, modifications of SVMs will be discussed in Sect. 6.2. Section 6.3 will focus on skew-insensitive decision trees. Variants of NN classifiers for imbalanced problems will be presented in Sect. 6.4 and skew insensitive Bayesian in Sect. 6.5. Finally, one-class cl作者: 遣返回國(guó) 時(shí)間: 2025-3-24 01:16
Ensemble Learning,e first introduce the foundations of ensemble learning and the most commonly considered ensemble methods for imbalanced problems, that is, Bagging and Boosting (Sect. 7.2). Then, we review the existing ensemble techniques in the framework of imbalanced datasets, focusing on two-class problems. Each 作者: cluster 時(shí)間: 2025-3-24 03:46
Imbalanced Classification with Multiple Classes,mbalanced problems are enumerated in Sect. 8.4. Next, a brief experimental study to contrast some of the state-of-the-art and promising approaches in this area is carried out in Sect. 8.5. Finally, the concluding remarks are given in Sect. 8.6.作者: mighty 時(shí)間: 2025-3-24 06:43
Dimensionality Reduction for Imbalanced Learning,ill also provide the recent advances in feature selection and feature extraction by non-linear methods. In addition, we will mention a recently proposed discretization approach which is able to reduce the numeric features into categories. The chapter is organized as follows. After a short introducti作者: 陰險(xiǎn) 時(shí)間: 2025-3-24 11:10 作者: correspondent 時(shí)間: 2025-3-24 17:10 作者: LARK 時(shí)間: 2025-3-24 20:23 作者: Aggregate 時(shí)間: 2025-3-25 00:08 作者: 純樸 時(shí)間: 2025-3-25 05:40 作者: ellagic-acid 時(shí)間: 2025-3-25 10:19
Alberto Fernández,Salvador García,Mikel Galar,Ronaldo C. Prati,Bartosz Krawczyk,Francisco Herrera attention recently.Topics treated include: Waves in piezoelectric crystals; Simulation of advanced BAW and SAW devices; Analysis of band gaps in phononic structures; Experimental investigation of phononic stru978-94-007-3342-8978-90-481-9893-1Series ISSN 1875-3507 Series E-ISSN 1875-3493 作者: FLORA 時(shí)間: 2025-3-25 14:40 作者: GUILT 時(shí)間: 2025-3-25 17:05
a straightforward way..This book also focuses on the data intrinsic characteristics that are the main causes?which, added to the uneven class distribution, truly hinders the performance of?classification algori978-3-030-07446-3978-3-319-98074-4作者: 陪審團(tuán)每個(gè)人 時(shí)間: 2025-3-25 23:01
es in anisotropic solids and/or electro-, magneto- interaction problems also regained much attention recently.Topics treated include: Waves in piezoelectric crystals; Simulation of advanced BAW and SAW devices; Analysis of band gaps in phononic structures; Experimental investigation of phononic stru作者: SEED 時(shí)間: 2025-3-26 04:06 作者: Adjourn 時(shí)間: 2025-3-26 05:17 作者: 擴(kuò)音器 時(shí)間: 2025-3-26 10:35 作者: FANG 時(shí)間: 2025-3-26 13:32 作者: FECK 時(shí)間: 2025-3-26 17:23
Alberto Fernández,Salvador García,Mikel Galar,Ronaldo C. Prati,Bartosz Krawczyk,Francisco Herrera then examined their physical properties and mechanical characteristics with regard to size effects. In our test results, the difference in ice strength according to the sample’s original location and orientation was small in an ice ridge model compared with level ice, suggesting that the ice ridge 作者: BILIO 時(shí)間: 2025-3-26 23:16 作者: 整潔 時(shí)間: 2025-3-27 03:23
Alberto Fernández,Salvador García,Mikel Galar,Ronaldo C. Prati,Bartosz Krawczyk,Francisco Herreras on the geometrical characteristics of the spiral. Vassilicos and Hunt[8] generalized these results to both fractals and spirals by showing that algebraic spirals have a well-defined Kolmogorov capacity (like fractals), and that a scalar field characterised by sharp interfaceswith well-defined Kolm作者: 興奮過(guò)度 時(shí)間: 2025-3-27 09:00 作者: Discrete 時(shí)間: 2025-3-27 10:04 作者: 魔鬼在游行 時(shí)間: 2025-3-27 15:06
Alberto Fernández,Salvador García,Mikel Galar,Ronaldo C. Prati,Bartosz Krawczyk,Francisco Herreraeneous turbulence, high vorticity regions are supposed to be a candidate of fine scale structure (She . 1990; Vincent and Meneguzzi, 1991; Jimenez .., 1993). However, definitions of fine scale structure based on vorticity magnitude are not clear and educed fine scale structures depend on the thresho作者: Aerate 時(shí)間: 2025-3-27 21:26 作者: terazosin 時(shí)間: 2025-3-27 23:18
Alberto Fernández,Salvador García,Mikel Galar,Ronaldo C. Prati,Bartosz Krawczyk,Francisco Herrerac. At the same time, improvements in experimental techniques have made available data that further necessitate efficient detection methods. A prominent example is the Particle Image Velocimetry (PIV) technique from which complex spatio-temporal flow data can be obtained. An interesting feature of so作者: ESO 時(shí)間: 2025-3-28 03:31
de. Quite a few important results on the modeling and simulation of Film Bulk Acoustic Resonator (FBAR) and Layered SAW devices were reported recently. The other recent advance of acoustic waves in solids is the so-called phononic crystals or phononic band-gap materials. Analogous to the band-gap of作者: Palpate 時(shí)間: 2025-3-28 07:23 作者: Between 時(shí)間: 2025-3-28 12:51
Alberto Fernández,Salvador García,Mikel Galar,Ronaldo C. Prati,Bartosz Krawczyk,Francisco Herrerade. Quite a few important results on the modeling and simulation of Film Bulk Acoustic Resonator (FBAR) and Layered SAW devices were reported recently. The other recent advance of acoustic waves in solids is the so-called phononic crystals or phononic band-gap materials. Analogous to the band-gap of作者: transdermal 時(shí)間: 2025-3-28 18:29 作者: fluoroscopy 時(shí)間: 2025-3-28 20:02 作者: assail 時(shí)間: 2025-3-29 01:15 作者: MENT 時(shí)間: 2025-3-29 05:39 作者: ROOF 時(shí)間: 2025-3-29 08:15 作者: 可轉(zhuǎn)變 時(shí)間: 2025-3-29 13:54
Alberto Fernández,Salvador García,Mikel Galar,Ronaldo C. Prati,Bartosz Krawczyk,Francisco Herrera long man-made hydraulic fractures in oil and gas reservoirs, or natural fractures, such as kilometers-long volcanic dikes driven by magma coming from upper mantle beneath the Earth’s crust. Different physical mechanisms governing propagation of a fluid-driven fracture include (i) dissipation in the作者: nominal 時(shí)間: 2025-3-29 17:21
Alberto Fernández,Salvador García,Mikel Galar,Ronaldo C. Prati,Bartosz Krawczyk,Francisco Herreraast decades, mainly because of their occurence in a wide variety of situations. For example, scalar fields rolled-up in a spiral way (Gilbert [2]), or displaying a fractal interface (Nicolleau [6]), are very common features of fluid flows. It has been recently shown that they might have remarkable p作者: CHASE 時(shí)間: 2025-3-29 23:29 作者: 檢查 時(shí)間: 2025-3-30 01:20 作者: 不能逃避 時(shí)間: 2025-3-30 05:42
Alberto Fernández,Salvador García,Mikel Galar,Ronaldo C. Prati,Bartosz Krawczyk,Francisco Herrera have made efforts to establish a theory of fine scale structure by assuming various type of structure as a fine scale structure (Townsend, 1951; Tennekes, 1968; Lundgren, 1982; Pullin and Saffman, 1993; Saffman and Pullin, 1994). Most of them are based on an assumption that many tubelike or sheet-l作者: negotiable 時(shí)間: 2025-3-30 08:51
Alberto Fernández,Salvador García,Mikel Galar,Ronaldo C. Prati,Bartosz Krawczyk,Francisco Herreraind a flow obstacle should have a significant effect on macroscopic parameters such as recirculation length or pressure drag. In the case of a flow over a fence with laminar inflow the shear layer separating from the leading edge of the flow obstacle will undergo transition to turbulence and the mai作者: fidelity 時(shí)間: 2025-3-30 15:04
Alberto Fernández,Salvador García,Mikel Galar,Ronaldo C. Prati,Bartosz Krawczyk,Francisco Herreracale of the surrounding small-scale turbulence. Organized structures may appear as secondary flows as a result of an instability but they persist in turbulent flows. They manifest themselves as eddies or localized vortices and play an important role in e.g. mixing and transport processes. Al- though作者: 釘牢 時(shí)間: 2025-3-30 19:23 作者: employor 時(shí)間: 2025-3-30 23:47
Foundations on Imbalanced Classification,es in the problem. This issue is known to hinder the performance of classifiers due to their accuracy oriented design, which usually makes the minority class to be overlooked. In this chapter the foundations on the class imbalance problem are introduced. Section 2.1 gives a formal description to imb作者: 落葉劑 時(shí)間: 2025-3-31 02:01
Performance Measures,y, the prevalence of more frequent classes may mask a poor classification performance in infrequent classes. To alleviate this problem, the choice of suitable measures is of fundamental importance. This chapter presents some performance measures that can be used to evaluate classification performanc
