A RECENT ADVANCE IN DATA ANALYSIS: Clustering Objects into Classes Characterized by Conjunctive Concepts

Michalski, Ryszard S.; Stepp, Robert E.; Diday, Edwin

doi:10.1016/b978-0-444-86325-6.50005-9

Cited by 82 publications

(36 citation statements)

References 4 publications

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“…When the attributes have substantially different ranges, the attributes can be normalized by dividing the individual attribute distances by the range or standard deviation of the attribute. A variety of other distance functions are also available for continuously-valued attributes, including the Minkowsky (Batchelor, 1978), Mahalanobis (Nadler & Smith, 1993), Camberra, Chebychev, Quadratic, Correlation, and Chi-square distance metrics (Michalski, Stepp, & Diday, 1981;Diday, 1974); the Context-Similarity measure (Biberman, 1994); the Contrast Model (Tversky, 1977); hyperrectangle distance functions (Salzberg, 1991;Domingos, 1995) and others. Several of these functions are defined in figure 1 (Wilson & Martinez, 1997a).…”

Section: Distance Functionmentioning

confidence: 99%

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2000

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Abstract. Instance-based learning algorithms are often faced with the problem of deciding which instances to store for use during generalization. Storing too many instances can result in large memory requirements and slow execution speed, and can cause an oversensitivity to noise. This paper has two main purposes. First, it provides a survey of existing algorithms used to reduce storage requirements in instance-based learning algorithms and other exemplar-based algorithms. Second, it proposes six additional reduction algorithms called DROP1-DROP5 and DEL (three of which were first described in Wilson & Martinez, 1997c, as RT1-RT3) that can be used to remove instances from the concept description. These algorithms and 10 algorithms from the survey are compared on 31 classification tasks. Of those algorithms that provide substantial storage reduction, the DROP algorithms have the highest average generalization accuracy in these experiments, especially in the presence of uniform class noise.

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Section: Distance Functionmentioning

confidence: 99%

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2000

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“…This layout tends to be "process-focused" since it is not optimised for the products; hence the process is more flexible but less efficient in comparison to "product-focused" layouts such as in the production of high volume electronics. [22], [23]. x ik denotes the value that the k th quantitative variable takes for the i th object (i=1,…,n; k=1,…,p) and w k (k=1,…p) are non-negative weights associated with the variables.…”

Section: Resultsmentioning

confidence: 99%

A case-based reasoning approach for low volume, high added value electronics

Segura-Velandia

West

Conway

et al. 2006

2006 8th Electronics Packaging Technology Conference

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“…The results thus obtained have been submitted to characterization analysis according to Ward's method (Ward, 1963) coupled with Chebychev's Euclidian distance (Diday, 1974;Michalski et al, 1981).…”

Section: Network Of Artificial Neurons and Hierarchical Classificationmentioning

confidence: 99%

Elaboration of a biotic index of pollution using macroinvertebrates for the monitoring of Lake Nokoué in Benin

Gnohossou¹,

Lalèyé²,

Atachi³

et al. 2016

Int. J. Bio. Chem. Sci

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A study on the relationships between the physicochemical parameters and of the macroinvertebrates of the Lake Nokoué was carried out for the purpose of developing a biotic index of pollution. A total of 96 stations were prospected twice during the flooding and the dry seasons from September 2004 to February 2006. At each station, seven physicochemical parameters were measured and macroinvertebrates were collected. Canonical analyses of correspondence were used to show the relations between the parameters of the environment and the macroinvertebrates. A self-organizing map (SOM) of Kohonen allows the categorization of the studied stations into four groups according to different degrees of pollution. Rough scores were allotted to each taxon according to its abundance in the various groups of stations determined by the SOM for each campaign. A synthesis of the data obtained from the four field surveys allows the assignment of a score to each taxon according to its abundance in the different groups of stations. A biotic index was developed and used for the evaluation of the level of pollution of the stations studied. It then emerged that the borders of the lake present a «poor quality» of water; however, during the dry season there is slight improvement.

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A RECENT ADVANCE IN DATA ANALYSIS: Clustering Objects into Classes Characterized by Conjunctive Concepts

Cited by 82 publications

References 4 publications

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A case-based reasoning approach for low volume, high added value electronics

Elaboration of a biotic index of pollution using macroinvertebrates for the monitoring of Lake Nokoué in Benin

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