Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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. Nº de ref. del artículo: 9786139908264
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Librería: Books Puddle, New York, NY, Estados Unidos de America
Condición: New. Nº de ref. del artículo: 26394698173
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Librería: Majestic Books, Hounslow, Reino Unido
Condición: New. Print on Demand. Nº de ref. del artículo: 401678946
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
Condición: New. PRINT ON DEMAND. Nº de ref. del artículo: 18394698167
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Librería: moluna, Greven, Alemania
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). . Nº de ref. del artículo: 385876831
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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. Nº de ref. del artículo: 9786139908264
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
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. Nº de ref. del artículo: 9786139908264
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Librería: preigu, Osnabrück, Alemania
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. Nº de ref. del artículo: 114835121
Cantidad disponible: 5 disponibles