標(biāo)題: Titlebook: Data Mining and Computational Intelligence; Abraham Kandel,Mark Last,Horst Bunke Book 2001 Physica-Verlag Heidelberg 2001 computational in [打印本頁] 作者: culinary 時間: 2025-3-21 19:46
書目名稱Data Mining and Computational Intelligence影響因子(影響力)
書目名稱Data Mining and Computational Intelligence影響因子(影響力)學(xué)科排名
書目名稱Data Mining and Computational Intelligence網(wǎng)絡(luò)公開度
書目名稱Data Mining and Computational Intelligence網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Mining and Computational Intelligence被引頻次
書目名稱Data Mining and Computational Intelligence被引頻次學(xué)科排名
書目名稱Data Mining and Computational Intelligence年度引用
書目名稱Data Mining and Computational Intelligence年度引用學(xué)科排名
書目名稱Data Mining and Computational Intelligence讀者反饋
書目名稱Data Mining and Computational Intelligence讀者反饋學(xué)科排名
作者: Medley 時間: 2025-3-21 21:29 作者: 表示向前 時間: 2025-3-22 02:59 作者: 因無茶而冷淡 時間: 2025-3-22 06:58
Mining Fuzzy Association Rules in a Database Containing Relational and Transactional Data,echnique for the mining of such rules in databases containing both types of data. This technique, which we call Fuzzy Miner, performs its tasks by the use of fuzzy logic, a set of transformation functions, and by residual analysis. With the transformation functions, new attributes and new item types作者: 落葉劑 時間: 2025-3-22 10:37
Fuzzy Linguistic Summaries via Association Rules,ata mining. Links between our approach to linguistic summaries and the well-known technique of association rules is shown. The generation of linguistic summaries is implemented by using the authors’ FQUERY for Access package.作者: 紅腫 時間: 2025-3-22 12:53
The Fuzzy-ROSA Method: A Statistically Motivated Fuzzy Approach for Data-Based Generation of Small for data-based rule generation has been demonstrated impressively in numerous real-world tasks. However, there are still difficulties in generating small interpretable rule bases efficiently, especially for applications with many input variables. The Fuzzy-ROSA method presented here was developed to作者: 紅腫 時間: 2025-3-22 17:41 作者: 樣式 時間: 2025-3-23 00:20 作者: grenade 時間: 2025-3-23 01:39
Mining a Growing Feature Map by Data Skeleton Modelling, knowledge discovery applications. In this article, we present a further extension to the GSOM in which the cluster identification process can be automated. The self-generating ability of the GSOM is used to identify the paths along which the GSOM grew, and these paths are used to develop a skeleton作者: 彎彎曲曲 時間: 2025-3-23 07:01
Some Practical Applications of Soft Computing and Data Mining,application areas, however, data is more complicated: real-life data is often obtained as an image from a camera rather than a few measurements. Furthermore, this image can also change dynamically. In this paper, we present several examples of how soft computing is related to mining such data.作者: ectropion 時間: 2025-3-23 11:11
Intelligent Mining in Image Databases, with Applications to Satellite Imaging and to Web Search,otos, a large amount of the information stored on the Web is in the form of images, etc. It is therefore desirable to use this image information in data mining. Unfortunately, most existing data mining techniques have been designed for mining numerical data and are thus not well suited for image dat作者: 使隔離 時間: 2025-3-23 14:56
Fuzzy Genetic Modeling and Forecasting for Nonlinear Time Series,eory as well as natural selection, and hence is called “genetic modeling”. In order to find a predictive model from the nonlinear time series, we make use of ‘survival of the fittest’ principle of evolution. Through the process of genetic evolution, the AIC criteria are used as the performance measu作者: 慢慢流出 時間: 2025-3-23 21:40 作者: Hyaluronic-Acid 時間: 2025-3-23 23:25 作者: 礦石 時間: 2025-3-24 04:24
Data Mining and Computational Intelligence978-3-7908-1825-3Series ISSN 1434-9922 Series E-ISSN 1860-0808 作者: cinder 時間: 2025-3-24 09:24
Post-Inflammatory Hyperpigmentationata mining. Links between our approach to linguistic summaries and the well-known technique of association rules is shown. The generation of linguistic summaries is implemented by using the authors’ FQUERY for Access package.作者: 愚蠢人 時間: 2025-3-24 12:04
Dale S. Huff MD,Dale S. Huff MDapplication areas, however, data is more complicated: real-life data is often obtained as an image from a camera rather than a few measurements. Furthermore, this image can also change dynamically. In this paper, we present several examples of how soft computing is related to mining such data.作者: 書法 時間: 2025-3-24 15:11
Fuzzy Linguistic Summaries via Association Rules,ata mining. Links between our approach to linguistic summaries and the well-known technique of association rules is shown. The generation of linguistic summaries is implemented by using the authors’ FQUERY for Access package.作者: 裂縫 時間: 2025-3-24 22:42 作者: 壓迫 時間: 2025-3-25 03:08
Pierre Russo MD,Pierre Russo MDThis chapter describes a method for knowledge discovery. First, we will describe the general approach to knowledge discovery, its characteristics and components. Then we will describe our method. Finally we will provide an example from the area of “economic modeling” to illustrate the use of soft regression in knowledge discovery.作者: 巨頭 時間: 2025-3-25 05:32 作者: landfill 時間: 2025-3-25 07:36
Maria Pia De Padova,Antonella Tostil research areas such as statistics, artificial intelligence, machine learning, and soft computing have contributed to the arsenal of methods for data mining. In this paper, however, we focus on neuro-fuzzy methods for rule learning. In our opinion, fuzzy approaches can play an important role in dat作者: macabre 時間: 2025-3-25 12:46 作者: 遠(yuǎn)足 時間: 2025-3-25 17:48 作者: 有幫助 時間: 2025-3-25 21:06
https://doi.org/10.1007/3-540-30223-9echnique for the mining of such rules in databases containing both types of data. This technique, which we call Fuzzy Miner, performs its tasks by the use of fuzzy logic, a set of transformation functions, and by residual analysis. With the transformation functions, new attributes and new item types作者: Fulsome 時間: 2025-3-26 04:07 作者: CLIFF 時間: 2025-3-26 08:20
Maria Pia De Padova,Antonella Tostifor data-based rule generation has been demonstrated impressively in numerous real-world tasks. However, there are still difficulties in generating small interpretable rule bases efficiently, especially for applications with many input variables. The Fuzzy-ROSA method presented here was developed to作者: GENUS 時間: 2025-3-26 10:24
J. Lakatos,K. K?ll?,G. Skaliczki,G. Holnapy practitioners. Many efficient algorithms have been proposed in the literature, e.g., Apriori, Partition, DIC, for mining association rules in the context of marketbasket analysis. They are all based on apriori methods, i.e., pruning the itemset lattice, and requires multiple database accesses. Howe作者: 雜役 時間: 2025-3-26 14:13
Metabolic and Endocrine Diseases,ning Technique (DPT1) generates a classifier model by the use of Single Attribute Partitioning Method and neural network training. Single Attribute Partitioning Technique partitions a single input dimension at a time using proportional analysis. The second Dimensional Partitioning Technique (DPT2), 作者: 粗鄙的人 時間: 2025-3-26 17:01 作者: 羽飾 時間: 2025-3-27 00:14
Dale S. Huff MD,Dale S. Huff MDapplication areas, however, data is more complicated: real-life data is often obtained as an image from a camera rather than a few measurements. Furthermore, this image can also change dynamically. In this paper, we present several examples of how soft computing is related to mining such data.作者: installment 時間: 2025-3-27 02:32
Dale S. Huff MD,Dale S. Huff MDotos, a large amount of the information stored on the Web is in the form of images, etc. It is therefore desirable to use this image information in data mining. Unfortunately, most existing data mining techniques have been designed for mining numerical data and are thus not well suited for image dat作者: 漂亮 時間: 2025-3-27 05:45
https://doi.org/10.1007/978-1-4614-0019-6eory as well as natural selection, and hence is called “genetic modeling”. In order to find a predictive model from the nonlinear time series, we make use of ‘survival of the fittest’ principle of evolution. Through the process of genetic evolution, the AIC criteria are used as the performance measu作者: Reclaim 時間: 2025-3-27 10:35 作者: Adenocarcinoma 時間: 2025-3-27 16:58
Studies in Fuzziness and Soft Computinghttp://image.papertrans.cn/d/image/262926.jpg作者: Ataxia 時間: 2025-3-27 21:22 作者: Psa617 時間: 2025-3-28 00:18
Maria Pia De Padova,Antonella Tostithe ensuing information granules. We propose two fundamental concepts in data mining: associations and rules. Associations are direction-free constructs that capture the most essential components of the overall structure in database. The relevance of associations is expressed by the cardinality of t作者: LAVA 時間: 2025-3-28 05:56 作者: Hectic 時間: 2025-3-28 07:55
Maria Pia De Padova,Antonella Tosti, rule search based on rule test and rating, on- and offline rule reduction and finally rule base analysis and optimization. With respect to the broad spectrum of applications, there are different methods available for each of these steps. An overview is given in the first part of this paper, with e作者: Pedagogy 時間: 2025-3-28 14:23
J. Lakatos,K. K?ll?,G. Skaliczki,G. Holnapyd FARD (Fuzzy Association Rule Discovery), for mining fuzzy association rules. FARD is based on the pruning of the fuzzy concept lattice, and can be applied equally to classical or fuzzy databases, by scanning the database only once.作者: 切掉 時間: 2025-3-28 16:45 作者: 發(fā)炎 時間: 2025-3-28 19:16 作者: BRAWL 時間: 2025-3-29 01:38
The Fuzzy-ROSA Method: A Statistically Motivated Fuzzy Approach for Data-Based Generation of Small , rule search based on rule test and rating, on- and offline rule reduction and finally rule base analysis and optimization. With respect to the broad spectrum of applications, there are different methods available for each of these steps. An overview is given in the first part of this paper, with e作者: contrast-medium 時間: 2025-3-29 06:28 作者: 微塵 時間: 2025-3-29 09:45 作者: Bereavement 時間: 2025-3-29 14:29
Fuzzy Genetic Modeling and Forecasting for Nonlinear Time Series,re, and the membership functions of the best-fitting models are the performance index of a chromosome. An empirical example shows that the genetic model can effectively find an intuitive model for nonlinear time series, especially when structure changes occur.作者: AGATE 時間: 2025-3-29 17:38 作者: 北京人起源 時間: 2025-3-29 23:19 作者: 難取悅 時間: 2025-3-30 01:47 作者: degradation 時間: 2025-3-30 06:15
Pierre Russo MD,Pierre Russo MDmated. The self-generating ability of the GSOM is used to identify the paths along which the GSOM grew, and these paths are used to develop a skeleton of the data set. Such a skeleton is then used as a base for separating the clusters in the data
