Isbn: 9786139908264 - applications of statistical tools in human daily activities (8 resultados)

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  • Idioma: Inglés

    6139908264 / 9786139908264

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    Librería: Books Puddle, Woodside, NY, Estados Unidos de AmericaBooks Puddle

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    Editorial: LAP LAMBERT Academic Publishing, 2018

    6139908264 / 9786139908264

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    Taschenbuch. Condición: Neu. Applications of Statistical Tools in Human Daily Activities | Oluwatosin Babasola (u. a.) | Taschenbuch | 56 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139908264 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Sep 2018, 2018

    6139908264 / 9786139908264

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Vital information is usually lost during ordinal classification problems that incur misclassification error which affects predictions. In an attempt to minimize this error, this study investigates the effectiveness of adopting Linear Quadratic Discriminant Analysis method in the classification of ordinal dataset problem involving three group cases. In predictions of Food Security Status, there is a need to employ a powerful statistical tool that can correctly classify a household based on the Food Consumption Scores Profile indicator into 'Poor', 'Borderline' and 'Acceptable'. The approach was used to classify food security status of two counties in region of Kenya. The summary classification results showed that 89.9% of the original grouped cases were correctly classified while 89.1% of the cross-validation grouped cases were correctly classified. This approach can be employed by major International Organizations and Government of nations in their quest to minimize hunger and starvation all over the world. 56 pp. Englisch.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2018

    6139908264 / 9786139908264

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    Librería: moluna, Greven, Alemaniamoluna

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    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Babasola OluwatosinBabasola O. LBSc, MSc Mathematics (Unilorin), MSc Mathematical Sciences (AIMS), MSc Fin. Maths (PAUSTI). .

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing

    6139908264 / 9786139908264

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    EUR 58,59

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    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Vital information is usually lost during ordinal classification problems that incur misclassification error which affects predictions. In an attempt to minimize this error, this study investigates the effectiveness of adopting Linear Quadratic Discriminant Analysis method in the classification of ordinal dataset problem involving three group cases. In predictions of Food Security Status, there is a need to employ a powerful statistical tool that can correctly classify a household based on the Food Consumption Scores Profile indicator into 'Poor', 'Borderline' and 'Acceptable'. The approach was used to classify food security status of two counties in region of Kenya. The summary classification results showed that 89.9% of the original grouped cases were correctly classified while 89.1% of the cross-validation grouped cases were correctly classified. This approach can be employed by major International Organizations and Government of nations in their quest to minimize hunger and starvation all over the world.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Sep 2018, 2018

    6139908264 / 9786139908264

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Vital information is usually lost during ordinal classification problems that incur misclassification error which affects predictions. In an attempt to minimize this error, this study investigates the effectiveness of adopting Linear Quadratic Discriminant Analysis method in the classification of ordinal dataset problem involving three group cases. In predictions of Food Security Status, there is a need to employ a powerful statistical tool that can correctly classify a household based on the Food Consumption Scores Profile indicator into 'Poor', 'Borderline' and 'Acceptable'. The approach was used to classify food security status of two counties in region of Kenya. The summary classification results showed that 89.9% of the original grouped cases were correctly classified while 89.1% of the cross-validation grouped cases were correctly classified. This approach can be employed by major International Organizations and Government of nations in their quest to minimize hunger and starvation all over the world.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.

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    6139908264 / 9786139908264

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    Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books

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  • Idioma: Inglés

    6139908264 / 9786139908264

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    Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios

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    EUR 65,27

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    Condición: New. PRINT ON DEMAND.