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Decision making and Feature reduction through Rough Sets - Butalia, Ayesha
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Butalia, Ayesha:
Decision making and Feature reduction through Rough Sets - Taschenbuch

ISBN: 3639328019

Gebundene Ausgabe, ID: 10402944

A new approach for feature selection, decision making for the areas of uncertainty - Buch, gebundene Ausgabe, 88 S., Beilagen: Paperback, Erschienen: 2011 VDM Verlag The issues of Real World are Very large data sets, Mixed types of data, Uncertainty, Incompleteness, Data change, Use of background knowledge etc. Lot of knowledge related to the application can be enerated through these large data sets. Rough set is the methodology which can be used to deduce rules from these data sets. It offers mathematical tools to discover patterns hidden in data and hence used in the field of data mining. Rough Sets does not require any preliminary information as Fuzzy sets require membership values or probability is required in statistics. Hence this is its specialty. Two novel algorithms to find optimal Reducts of condition attributes based on the relative attribute dependency, out of which the first algorithms gives simple Reduct whereas the second one gives the Reduct with minimum attributes, and highlights on the case study of mushroom which consists of twenty two attributes depending on which the decision is taken whether the mushroom plant is edible or poisonous.

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Decision making and Feature reduction through Rough Sets - Ayesha Butalia
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Ayesha Butalia:
Decision making and Feature reduction through Rough Sets - Taschenbuch

2011, ISBN: 3639328019

ID: 10407751898

[EAN: 9783639328011], Neubuch, [PU: VDM Verlag Mrz 2011], This item is printed on demand - Print on Demand Titel. Neuware - The issues of Real World are Very large data sets, Mixed types of data, Uncertainty, Incompleteness, Data change, Use of background knowledge etc. Lot of knowledge related to the application can be enerated through these large data sets. Rough set is the methodology which can be used to deduce rules from these data sets. It offers mathematical tools to discover patterns hidden in data and hence used in the field of data mining. Rough Sets does not require any preliminary information as Fuzzy sets require membership values or probability is required in statistics. Hence this is its specialty. Two novel algorithms to find optimal Reducts of condition attributes based on the relative attribute dependency, out of which the first algorithms gives simple Reduct whereas the second one gives the Reduct with minimum attributes, and highlights on the case study of mushroom which consists of twenty two attributes depending on which the decision is taken whether the mushroom plant is edible or poisonous. 88 pp. Englisch

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Decision making and Feature reduction through Rough Sets - Ayesha Butalia
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Decision making and Feature reduction through Rough Sets - neues Buch

ISBN: 9783639328011

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The issues of Real World are Very large data sets, Mixed types of data, Uncertainty, Incompleteness, Data change, Use of background knowledge etc. Lot of knowledge related to the application can be enerated through these large data sets. Rough set is the methodology which can be used to deduce rules from these data sets. It offers mathematical tools to discover patterns hidden in data and hence used in the field of data mining. Rough Sets does not require any preliminary information as Fuzzy sets require membership values or probability is required in statistics. Hence this is its specialty. Two novel algorithms to find optimal Reducts of condition attributes based on the relative attribute dependency, out of which the first algorithms gives simple Reduct whereas the second one gives the Reduct with minimum attributes, and highlights on the case study of mushroom which consists of twenty two attributes depending on which the decision is taken whether the mushroom plant is edible or poisonous. Bücher / Naturwissenschaften, Medizin, Informatik & Technik / Informatik & EDV, [PU: VDM Verlag Dr. Müller, Saarbrücken]

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Decision making and Feature reduction through Rough Sets - Butalia, Ayesha
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Butalia, Ayesha:
Decision making and Feature reduction through Rough Sets - Taschenbuch

2011, ISBN: 9783639328011

[ED: Softcover], [PU: Vdm Verlag Dr. Müller], The issues of Real World are Very large data sets, Mixed types of data, Uncertainty, Incompleteness, Data change, Use of background knowledge etc. Lot of knowledge related to the application can be enerated through these large data sets. Rough set is the methodology which can be used to deduce rules from these data sets. It offers mathematical tools to discover patterns hidden in data and hence used in the field of data mining. Rough Sets does not require any preliminary information as Fuzzy sets require membership values or probability is required in statistics. Hence this is its specialty. Two novel algorithms to find optimal Reducts of condition attributes based on the relative attribute dependency, out of which the first algorithms gives simple Reduct whereas the second one gives the Reduct with minimum attributes, and highlights on the case study of mushroom which consists of twenty two attributes depending on which the decision is taken whether the mushroom plant is edible or poisonous.2011. 88 S.Versandfertig in 3-5 Tagen, [SC: 0.00]

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Decision making and Feature reduction through Rough Sets - Butalia, Ayesha
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Butalia, Ayesha:
Decision making and Feature reduction through Rough Sets - Taschenbuch

2011, ISBN: 3639328019

Gebundene Ausgabe, ID: 10402944

A new approach for feature selection, decision making for the areas of uncertainty - Buch, gebundene Ausgabe, 88 S., Beilagen: Paperback, Erschienen: 2011 VDM Verlag, [PU: VDM Verlag Dr. Müller, Saarbrücken]

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Details zum Buch
Decision making and Feature reduction through Rough Sets

The issues of Real World are Very large data sets, Mixed types of data, Uncertainty, Incompleteness, Data change, Use of background knowledge etc. Lot of knowledge related to the application can be enerated through these large data sets. Rough set is the methodology which can be used to deduce rules from these data sets. It offers mathematical tools to discover patterns hidden in data and hence used in the field of data mining. Rough Sets does not require any preliminary information as Fuzzy sets require membership values or probability is required in statistics. Hence this is its specialty. Two novel algorithms to find optimal Reducts of condition attributes based on the relative attribute dependency, out of which the first algorithms gives simple Reduct whereas the second one gives the Reduct with minimum attributes, and highlights on the case study of mushroom which consists of twenty two attributes depending on which the decision is taken whether the mushroom plant is edible or poisonous.

Detailangaben zum Buch - Decision making and Feature reduction through Rough Sets


EAN (ISBN-13): 9783639328011
ISBN (ISBN-10): 3639328019
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2011
Herausgeber: VDM Verlag Mrz 2011

Buch in der Datenbank seit 11.01.2007 15:21:29
Buch zuletzt gefunden am 20.06.2017 08:16:34
ISBN/EAN: 3639328019

ISBN - alternative Schreibweisen:
3-639-32801-9, 978-3-639-32801-1


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