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標題: Titlebook: Outlier Analysis; Charu C. Aggarwal Textbook 2017Latest edition Springer International Publishing AG 2017 Outlier Analysis.Anomaly detecti [打印本頁]

作者: 契約    時間: 2025-3-21 17:27
書目名稱Outlier Analysis影響因子(影響力)




書目名稱Outlier Analysis影響因子(影響力)學科排名




書目名稱Outlier Analysis網(wǎng)絡公開度




書目名稱Outlier Analysis網(wǎng)絡公開度學科排名




書目名稱Outlier Analysis被引頻次




書目名稱Outlier Analysis被引頻次學科排名




書目名稱Outlier Analysis年度引用




書目名稱Outlier Analysis年度引用學科排名




書目名稱Outlier Analysis讀者反饋




書目名稱Outlier Analysis讀者反饋學科排名





作者: CURB    時間: 2025-3-21 23:49

作者: overweight    時間: 2025-3-22 04:25

作者: Foam-Cells    時間: 2025-3-22 08:09
Charu C. Aggarwal types can be reduced to three principles: ciliary and ameboid movements and muscle contraction..The ultrastructure of all kinds of cilia is very similar from single cell organisms to highly specialized cells of the human body, e.g., ciliary respiratory epithelium. As a rule, ciliary movement is cau
作者: pericardium    時間: 2025-3-22 09:18
Charu C. Aggarwal?ngen auftreten, sondern vor allem weil sie miteinander in einer engen Wechselbeziehung stehen. Diese beiden Grenzwertbildungen, das . und der ., wurden an Hand vereinzelter Beispiele schon seit langer Zeit, z. T. sogar schon im klassischen Altertum betrachtet ; aber erst die Tatsache, da? man ihren
作者: indicate    時間: 2025-3-22 16:36
Charu C. Aggarwal?ngen auftreten, sondern vor allem weil sie miteinander in einer engen Wechselbeziehung stehen. Diese beiden Grenzwertbildungen, das . und der ., wurden an Hand vereinzelter Beispiele schon seit langer Zeit, z. T. sogar schon im klassischen Altertum betrachtet ; aber erst die Tatsache, da? man ihren
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Linear Models for Outlier Detection,f prediction and anomaly detection are intimately related. Outliers are, after all, values that deviate from expected (or .) values on the basis of a particular model. Linear models focus on the use of interattribute dependencies to achieve this goal. In the classical statistics literature, this pro
作者: 集合    時間: 2025-3-23 06:12

作者: 同謀    時間: 2025-3-23 11:10
Outlier Ensembles, algorithms or . to create a unified output. The basic idea of the approach is that some algorithms will do well on a particular subset of points whereas other algorithms will do better on other subsets of points. However, the ensemble combination is often able to perform more robustly across the bo
作者: 性上癮    時間: 2025-3-23 15:58
Supervised Outlier Detection,bnormalities in the data. In such scenarios, many of the anomalies found correspond to noise or other uninteresting phenomena. It has been observed [338, 374, 531] in diverse applications such as system anomaly detection, financial fraud, and Web robot detection that .. In such cases, an unsupervise
作者: flimsy    時間: 2025-3-23 18:33
Outlier Detection in Categorical, Text, and Mixed Attribute Data,ication because categorical attributes are ubiquitous in real-world data. For example, although demographic data may contain quantitative attributes such as the age, most other attributes such as gender, race, and ZIP code are categorical. Data collected from surveys may often contain responses to m
作者: 元音    時間: 2025-3-23 23:17

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作者: Suppository    時間: 2025-3-24 07:57
Spatial Outlier Detection,temporal attributes to occur in various combinations of behavioral and contextual attributes. Such data is also referred to as . data. For example, in some applications, such as hurricane tracking, the contextual attributes are both spatial and temporal.
作者: 銀版照相    時間: 2025-3-24 12:51
Applications of Outlier Analysis,etection, Web analytics, and medical diagnosis. The applications of outlier analysis are so diverse that it is impossible to exhaustively cover all possibilities in a single chapter. Therefore, the goal of this chapter is to cover many problem domains at a higher level and show how they map to the v
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作者: TIGER    時間: 2025-3-25 21:34
Proximity-Based Outlier Detection,Proximity-based techniques define a data point as an outlier when its locality (or .) is sparsely populated. The proximity of a data point may be defined in a variety of ways, which are subtly different from one another but are similar enough to merit unified treatment within a single chapter.
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作者: 旅行路線    時間: 2025-3-26 05:55

作者: 笨重    時間: 2025-3-26 09:33
Supervised Outlier Detection,ases, different types of abnormal instances could be present, and it may be desirable to distinguish among them. For example, in an intrusion-detection scenario, different types of intrusion anomalies are possible, and the specific type of an intrusion is important information.
作者: Cumbersome    時間: 2025-3-26 15:55
Outlier Detection in Categorical, Text, and Mixed Attribute Data,rently categorical. In many cases, categorical and numeric attributes are found in the same data set. Such . are often challenging to machine-learning applications because of the difficulties in treating the various types of attributes in a homogeneous and consistent way.
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作者: PHONE    時間: 2025-3-27 06:42
Probabilistic and Statistical Models for Outlier Detection,s such as data representation or computational efficiency. Nevertheless, the underlying mathematical models are extremely useful and have eventually been adapted to a variety of computational scenarios.
作者: 債務    時間: 2025-3-27 11:24
Outlier Ensembles,ard because of its ability to combine the outputs of multiple algorithms. In this chapter, will use the terms . and . interchangeably to denote the individual algorithms whose outputs are combined to create the final result.
作者: 場所    時間: 2025-3-27 17:13
Applications of Outlier Analysis,arious techniques discussed in earlier chapters. The practical issues and challenges in the context of real data sets will also be discussed. This will provide a broader understanding of the issues involved in ..
作者: FATAL    時間: 2025-3-27 21:10
ights into when and why particular algorithms work effectiveThis book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the computational framework and therefore appe
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re detailed and is written to appeal to both researchers and practitioners. Significant new material has been added on topics such as kernel methods, one-class support-vector machines, matrix factorization, neu978-3-319-83772-7978-3-319-47578-3
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Jürgen Boelcke,Bernard Straub,Paul Thiele) and erosion contact algorithm, to accurately predict the large strain developed in target plate due to impact of different fragment shapes (spherical and conical). The simulation results of spherical fragment shape are corroborated with literature experimental observations. The lower fragment perf
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作者: 大火    時間: 2025-3-30 00:03
,Few Shot NER on?Augmented Unstructured Text from?Cardiology Records,entists, machine learning engineers, and web developers, who have little or no knowledge about building web apps that implement bootstrap technologies. After completing this book, you will have th978-1-4842-7782-9978-1-4842-7783-6
作者: 諷刺    時間: 2025-3-30 08:01
Gordan Djurdjevica common usage in formal language theory, most of the proofs of computability are reduced to the semi-formal description of a procedure the constructivity of which is apparent to anybody having some programming experience. Notwithstanding these facts the subject is treated with mathematical rigor; a
作者: 專心    時間: 2025-3-30 11:07
Numbers II Building the Integers and Building with the Integers,to manipulate them. The current chapter builds on those basics with the help of the material in the intervening chapters, which have given us advanced tools for discussing and manipulating numbers and aggregations of numbers.
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ty of cities to drive the needed transformative change by regenerating past damage to natural and social environments and seizing the opportunity to become greener, healthier and more equitable in the post-pandemic recovery and beyond. The study guided by the premise -.- shed light on the importance




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