標(biāo)題: Titlebook: Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques; Evangelos Triantaphyllou,Giovanni Felici Book 2006 Spri [打印本頁] 作者: Agoraphobia 時間: 2025-3-21 20:02
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書目名稱Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques讀者反饋學(xué)科排名
作者: Encumber 時間: 2025-3-22 00:19 作者: 色情 時間: 2025-3-22 02:19 作者: debble 時間: 2025-3-22 08:32 作者: 使乳化 時間: 2025-3-22 09:24 作者: figment 時間: 2025-3-22 14:01
Yujiro Nishioka,Junichi Shindohecision tree induction (SODI) algorithm, which uses conjunctive and disjunctive combinations of two attributes for improved decision tree induction in nominal databases. We show via numerical examples that in many cases this generates more accurate classification models and easier to interpret decision trees and rules.作者: figment 時間: 2025-3-22 17:34
Run-Time Data Structures in GPenSIMer is interested. We apply fuzzy rules to adapt user queries by fuzzy inference within a sound and complete fuzzy logic system. We show some empirical results indicating that using our unified framework, the induction and application of fuzzy rules produces a more effective textual information retrieval system.作者: CAJ 時間: 2025-3-22 23:46 作者: 燈絲 時間: 2025-3-23 02:46
Rule Induction Through Discrete Support Vector Decision Trees,ilt by means of a multivariate split derived at each node from the approximate solution of the discrete SVM. Computational tests on well-known benchmark datasets indicate that our classifier achieves a superior trade-off between accuracy and complexity of the induced rules, outperforming other competing approaches.作者: 討厭 時間: 2025-3-23 07:32
Multi-Attribute Decision Trees and Decision Rules,ecision tree induction (SODI) algorithm, which uses conjunctive and disjunctive combinations of two attributes for improved decision tree induction in nominal databases. We show via numerical examples that in many cases this generates more accurate classification models and easier to interpret decision trees and rules.作者: Initial 時間: 2025-3-23 09:48
Induction and Inference with Fuzzy Rules for Textual Information Retrieval,er is interested. We apply fuzzy rules to adapt user queries by fuzzy inference within a sound and complete fuzzy logic system. We show some empirical results indicating that using our unified framework, the induction and application of fuzzy rules produces a more effective textual information retrieval system.作者: enflame 時間: 2025-3-23 15:21 作者: hematuria 時間: 2025-3-23 19:58
P. Earnshaw,A. Busuttil,A. Fergusonnal numbers to . values uses a technique called Outpoint that determines abrupt changes of classification cases. The methods of this chapter are rather new and have been found to be effective and reliable in preliminary tests.作者: 假 時間: 2025-3-24 00:08
Deborah S. Keller,Scott R. Steeleness, statistics and logic implication, (3) to fuzzy/partially satisfied functional dependencies for handling data closeness and noise tolerance, and (4) to time-series data patterns that are associated with partial degrees.作者: Armory 時間: 2025-3-24 03:17
Daniel L. Feingold,Steven A. Lee-Kongd. The essence of each method is presented. Moreover, we discuss selected studies that address most of the necessary conditions for a fuzzy model to be interpretable and highlight areas for future studies. To give an idea of where fuzzy modeling methods have been applied, major application areas are also summarized.作者: Promotion 時間: 2025-3-24 07:57
Activity-Oriented Petri Nets (AOPN)the application area of record linkage, followed by a description of the Fellegi-Sunter model of record linkage. The chapter then shows how to estimate the appropriate Bayesian generalized linear model with latent classes, and, using the posterior kernels, determine the final decision rule.作者: animated 時間: 2025-3-24 13:00 作者: CEDE 時間: 2025-3-24 15:13 作者: 疲憊的老馬 時間: 2025-3-24 20:27
Mining Human Interpretable Knowledge with Fuzzy Modeling Methods: An Overview,d. The essence of each method is presented. Moreover, we discuss selected studies that address most of the necessary conditions for a fuzzy model to be interpretable and highlight areas for future studies. To give an idea of where fuzzy modeling methods have been applied, major application areas are also summarized.作者: 配偶 時間: 2025-3-25 01:42
Statistical Rule Induction in the Presence of Prior Information: The Bayesian Record Linkage Problethe application area of record linkage, followed by a description of the Fellegi-Sunter model of record linkage. The chapter then shows how to estimate the appropriate Bayesian generalized linear model with latent classes, and, using the posterior kernels, determine the final decision rule.作者: Barrister 時間: 2025-3-25 04:28
The One Clause at a Time (OCAT) Approach to Data Mining and Knowledge Discovery,ing large scale data mining problems, and a way of how to generate the next best example to consider for training. The later methods can be combined with any Boolean function learning method and are not restricted to the OCAT approach only.作者: 灌溉 時間: 2025-3-25 07:46 作者: MAG 時間: 2025-3-25 12:02
https://doi.org/10.1007/0-387-34296-6BAYES; Data mining; Knowledge discovery; LA; Pattern Recognition; Rule induction; STATISTICA作者: CHANT 時間: 2025-3-25 16:59
978-1-4419-4173-2Springer-Verlag US 2006作者: OATH 時間: 2025-3-25 21:55
Evangelos Triantaphyllou,Giovanni FeliciProvides a unique perspective into the core of data mining and knowledge discovery (DM and KD), combining many theoretical foundations for the behavior and capabilities of various DM and KD methods.In作者: Presbyopia 時間: 2025-3-26 00:23 作者: abject 時間: 2025-3-26 05:05 作者: output 時間: 2025-3-26 09:00 作者: 獨特性 時間: 2025-3-26 16:31 作者: 按等級 時間: 2025-3-26 18:24
Clinical Diagnosis of Colorectal Cancers of rules is implicative but these rules can be represented in different forms. The model of knowledge base and an example of the reasoning process based on knowledge are considered. An approach is proposed for inferring implicative logical rules from examples. The concept of a good diagnostic test作者: 合適 時間: 2025-3-26 22:13 作者: 真實的你 時間: 2025-3-27 04:06
David T. Rubin,Abraham H. Dachmanhod derives from given training data certain minimum cost satisfiability problems, solves these problems, and deduces from the solutions the desired logic formulas. There are at least two ways in which the results may be employed. First, one may use the logic formulas directly as rules in applicatio作者: Anemia 時間: 2025-3-27 06:01
Preoperative Staging of Rectal Cancer order to obtain a more essential and compact representation of the available information. The selected subset has to be small in size and must retain the information that is most useful for the specific application. The role of Feature Selection is particularly important when computationally expens作者: ORE 時間: 2025-3-27 13:16
P. Earnshaw,A. Busuttil,A. Fergusonormula constructors, so that records can be processed that contain rational number and/or nominal values. A nominal value is an element or subset of a given finite set. In such cases, the rational numbers or nominal values must first be transformed to . values before the method may be applied. This 作者: 遺產(chǎn) 時間: 2025-3-27 16:33 作者: 先驅(qū) 時間: 2025-3-27 17:50 作者: creditor 時間: 2025-3-27 23:57
Yujiro Nishioka,Junichi Shindohtop-down induction of decision trees is one of the most popular techniques for inducing such classification models. Most of the research in decision tree induction has focused on single attribute trees, but in this chapter we review multi-attribute decision trees induction and discuss how such metho作者: forbid 時間: 2025-3-28 05:23
One Operation for Double Pathologyl organisms. This ability relies heavily on the quality of the raw information available about the target system. In reality, these raw information/data may contain uncertainty and fuzziness, that is, it may be imprecise or incomplete. A number of techniques, such as the Dempster-Shafer theory of be作者: LATE 時間: 2025-3-28 08:05
Blind Pouch Syndrome After Bowel Resectionses on discovering accurate, comprehensible rules. In this chapter we also take these two criteria into account, but we go beyond them in the sense that we aim at discovering rules that are interesting (surprising) for the user. Hence, the search for rules is guided by a rule-evaluation function tha作者: PAC 時間: 2025-3-28 13:49 作者: 馬籠頭 時間: 2025-3-28 15:27
Deborah S. Keller,Scott R. Steele years have witnessed many efforts on discovering fuzzy associations, aimed at coping with fuzziness in knowledge representation and decision support processes. This chapter focuses on associations of three kinds: association rules, functional dependencies and pattern associations. Accordingly, it o作者: 可行 時間: 2025-3-28 19:49 作者: 切碎 時間: 2025-3-29 00:14 作者: commute 時間: 2025-3-29 07:08
Activity-Oriented Petri Nets (AOPN)word “sight” might become the word “site.” A spell checker cannot identify such an error. In the English language—the case of interest here—a syntax checker may also fail to catch such an error since, among other reasons, the parts-of-speech of an erroneous word may permit an acceptable parsing. Thi作者: 名次后綴 時間: 2025-3-29 09:16
Run-Time Data Structures in GPenSIM. Fuzzy rules are extracted from the fuzzy clusters discovered by the fuzzy C-means clustering method. These rules can be used to characterize the semantical connections between keywords in a set of textual documents, and thus the rules can be used to improve the user queries for better retrieval pe作者: 流出 時間: 2025-3-29 13:21
Activity-Oriented Petri Nets (AOPN)sification rule as a decision to link or not to link two records in different databases in the absence of a common identifier. When a training data set of classified cases is available, developing a rule is easy; this chapter expands the application of the technique to situations where a training da作者: 六個才偏離 時間: 2025-3-29 15:48
A Common Logic Approach to Data Mining and Pattern Recognition,of Boolean or multi-valued attributes for modeling of the natural subject areas. Inductive inference used for extracting knowledge from data is combined with deductive inference, which solves other pattern recognition problems. A set of efficient algorithms was developed to solve the regarded proble作者: 坦白 時間: 2025-3-29 21:41
The One Clause at a Time (OCAT) Approach to Data Mining and Knowledge Discovery,mathematical logic and discrete optimization. As input it uses samples of the performance of the system (or phenomenon) under consideration and then it extracts its underlying behavior in terms of a compact and rather accurate set of classification rules. This chapter also provides ways for decompos作者: 無能力 時間: 2025-3-30 00:30 作者: debacle 時間: 2025-3-30 06:41 作者: stroke 時間: 2025-3-30 11:01 作者: 小步舞 時間: 2025-3-30 14:46
Feature Selection for Data Mining, order to obtain a more essential and compact representation of the available information. The selected subset has to be small in size and must retain the information that is most useful for the specific application. The role of Feature Selection is particularly important when computationally expens作者: 保全 時間: 2025-3-30 17:51
Transformation of Rational Data and Set Data to Logic Data,ormula constructors, so that records can be processed that contain rational number and/or nominal values. A nominal value is an element or subset of a given finite set. In such cases, the rational numbers or nominal values must first be transformed to . values before the method may be applied. This 作者: Cpap155 時間: 2025-3-30 21:20
Data Farming: Concepts and Methods,data required for archival purposes. In some cases, the set of considered features might be large (a wide data set) and sufficient for extraction of knowledge. In other cases the data set might be narrow and insufficient to extract meaningful knowledge or the data may not even exist..Mining wide dat作者: 甜瓜 時間: 2025-3-31 03:20 作者: Defiance 時間: 2025-3-31 08:59
Multi-Attribute Decision Trees and Decision Rules,top-down induction of decision trees is one of the most popular techniques for inducing such classification models. Most of the research in decision tree induction has focused on single attribute trees, but in this chapter we review multi-attribute decision trees induction and discuss how such metho作者: 間諜活動 時間: 2025-3-31 09:42
Knowledge Acquisition and Uncertainty in Fault Diagnosis: A Rough Sets Perspective,l organisms. This ability relies heavily on the quality of the raw information available about the target system. In reality, these raw information/data may contain uncertainty and fuzziness, that is, it may be imprecise or incomplete. A number of techniques, such as the Dempster-Shafer theory of be作者: Redundant 時間: 2025-3-31 16:31 作者: Cultivate 時間: 2025-3-31 19:33
Diversity Mechanisms in Pitt-Style Evolutionary Classifier Systems,yze the effects of implicit fitness sharing, spatially distributed subpopulations, and combinations of the two, using a range of standard knowledge discovery tasks. The proposed models are compared based on (a) their ability to promote and/or maintain diversity across the evolving population; (b) th作者: 無畏 時間: 2025-3-31 21:58 作者: 燒烤 時間: 2025-4-1 02:37
Mining Human Interpretable Knowledge with Fuzzy Modeling Methods: An Overview,zy decision trees that can be easily understood by a human. Past studies on generating fuzzy If-Then rules (mostly from exemplar crisp data and a few from exemplar fuzzy data) are grouped into six major categories: grid partitioning, fuzzy clustering, genetic algorithms, neural networks, hybrid meth作者: 與野獸博斗者 時間: 2025-4-1 08:41 作者: Kinetic 時間: 2025-4-1 10:36
Learning to Find Context Based Spelling Errors,word “sight” might become the word “site.” A spell checker cannot identify such an error. In the English language—the case of interest here—a syntax checker may also fail to catch such an error since, among other reasons, the parts-of-speech of an erroneous word may permit an acceptable parsing. Thi作者: 水獺 時間: 2025-4-1 15:17 作者: RECUR 時間: 2025-4-1 19:19
Statistical Rule Induction in the Presence of Prior Information: The Bayesian Record Linkage Problesification rule as a decision to link or not to link two records in different databases in the absence of a common identifier. When a training data set of classified cases is available, developing a rule is easy; this chapter expands the application of the technique to situations where a training da作者: Accord 時間: 2025-4-2 00:26 作者: employor 時間: 2025-4-2 05:17
