Martin aruldoss (43 risultati)

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

Condizione: New. In English.

Condizione: New.

Taschenbuch. Condizione: Neu. Reference Model for Business Intelligence to Predict Bankruptcy | A Stepwise Comprehensive Solution for Business Intelligence: Model, Architecture and Application | Martin Aruldoss (u. a.) | Taschenbuch | 272 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659773150 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condizione: New.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: Hervorragend. Zustand: Hervorragend | Produktart: Bücher | Künstliche Intelligenz (KI), die von neuronalen Netzen gesteuert wird, ist für viele Anwendungen wie Empfehlungssysteme, Sprachübersetzung, soziale Medien, Chatbots und Rechtschreibprüfung usw. von entscheidender Bedeutung. Diese Netze werden jedoch häufig als "Blackboxen" kritisiert, was Bedenken hinsichtlich ihrer Erklärbarkeit aufkommen lässt, insbesondere in sensiblen Bereichen wie dem Gesundheitswesen, dem autonomen Fahren usw. Bestehende Methoden zur Verbesserung der Erklärbarkeit, wie z. B. die Bedeutung von Merkmalen, sind oft nicht klar und leicht zu interpretieren. Um dieses Problem zu lösen, wurde das objektorientierte neuronale Netz zur Verbesserung der Erklärbarkeit (OONNIE) entwickelt. OONNIE verwendet objektorientierte Modellierung, um Verlust- und Verbindungsgewicht zur Berechnung der Merkmalsbedeutung zu kombinieren und integriert domänenspezifische Regeln durch die Erweiterbarkeit von OOP. Das Modell betont die algorithmische Transparenz, indem jeder Trainingsschritt detailliert beschrieben wird. Bei der Evaluierung von XOR- und XNOR-Funktionen zeigt OONNIE vielversprechende Ergebnisse bei der Merkmalsbedeutung, eine schnellere Verlustreduzierung und verbesserte Vorhersagen nach der Integration von Domänenregeln. Dies ist ein wichtiger Beitrag zur erklärbaren KI und macht OONNIE zu einem wertvollen Werkzeug für die Entwicklung vertrauenswürdiger KI-Systeme.…

Softcover. Condizione: gut. 2025. Verbesserung der Erklärbarkeit von neuronalen Netzen: In Bezug auf die Wichtigkeit der Merkmale, die Regeln des Bereichs und die Transparenz der Algorithmen In deutscher Sprache. pages.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Bankruptcy is a financial failure of a business or an organization. It leads to catastrophic results to the whole community. Different kinds of bankruptcy prediction techniques are proposed to predict it. But, they are restricted as techniques in predicting the bankruptcy and not addressing the associated activities like acquiring the suitable data and delivering the results to the user after processing it. This situation demands to look for a comprehensive solution for predicting bankruptcy with intelligence. In this book, to model a comprehensive intelligence solution for bankruptcy prediction a Reference Model for buSiness inTelligence to prEdict bankruPtcy (RM-STEP) is designed by applying unit operations as hierarchical structure with abstract components. To realize the proposed reference model, ARCHitecture for buSiness inTelligence to prEdict bankruPtcy (ARCH-STEP) has been designed. Research experiment is designed for ARCH-STEP and the architectural experience of applying RM-STEP is reported. This book is essential toolkit for bankers, business executives, software architects, BI professionals and researchers who wish to provide the BI solution for various domains. 272 pp. Englisch.…

Condizione: New. Print on Demand.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Aruldoss MartinAruldoss Martin received the Ph.D. in CSE(Banking Technology). His research interests include business intelligence and multi-criteria reporting and received 129 citations for his publications in these areas since 2010.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial Intelligence (AI) driven by neural networks is crucial in many applications like recommendation systems, language translation, social media, chatbots, and spell-checking etc. However, these networks are often criticized for being 'black boxes,' raising concerns about their explainability, especially in sensitive domains like healthcare, autonomous driving etc. Existing methods to enhance explainability, such as feature importance, often lack clarity and interpretability.To address this, the Object-Oriented Neural Network for Improved Explainability (OONNIE) was developed. OONNIE uses object-oriented modeling to combine loss and connection weight for computing feature importance and integrates domain-specific rules through OOP's extendability. The model emphasizes algorithmic transparency by detailing every training step. Evaluated on XOR and XNOR functions, OONNIE shows promising results in feature importance, faster loss reduction, and improved predictions after integrating domain rules. This marks a significant contribution to explainable AI, making OONNIE a valuable tool for developing trustworthy AI systems.…

Condizione: New. PRINT ON DEMAND.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Bankruptcy is a financial failure of a business or an organization. It leads to catastrophic results to the whole community. Different kinds of bankruptcy prediction techniques are proposed to predict it. But, they are restricted as techniques in predicting the bankruptcy and not addressing the associated activities like acquiring the suitable data and delivering the results to the user after processing it. This situation demands to look for a comprehensive solution for predicting bankruptcy with intelligence. In this book, to model a comprehensive intelligence solution for bankruptcy prediction a Reference Model for buSiness inTelligence to prEdict bankruPtcy (RM-STEP) is designed by applying unit operations as hierarchical structure with abstract components. To realize the proposed reference model, ARCHitecture for buSiness inTelligence to prEdict bankruPtcy (ARCH-STEP) has been designed. Research experiment is designed for ARCH-STEP and the architectural experience of applying RM-STEP is reported. This book is essential toolkit for bankers, business executives, software architects, BI professionals and researchers who wish to provide the BI solution for various domains.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 272 pp. Englisch. …

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Bankruptcy is a financial failure of a business or an organization. It leads to catastrophic results to the whole community. Different kinds of bankruptcy prediction techniques are proposed to predict it. But, they are restricted as techniques in predicting the bankruptcy and not addressing the associated activities like acquiring the suitable data and delivering the results to the user after processing it. This situation demands to look for a comprehensive solution for predicting bankruptcy with intelligence. In this book, to model a comprehensive intelligence solution for bankruptcy prediction a Reference Model for buSiness inTelligence to prEdict bankruPtcy (RM-STEP) is designed by applying unit operations as hierarchical structure with abstract components. To realize the proposed reference model, ARCHitecture for buSiness inTelligence to prEdict bankruPtcy (ARCH-STEP) has been designed. Research experiment is designed for ARCH-STEP and the architectural experience of applying RM-STEP is reported. This book is essential toolkit for bankers, business executives, software architects, BI professionals and researchers who wish to provide the BI solution for various domains. …

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - La Inteligencia Artificial (IA) impulsada por redes neuronales es crucial en muchas aplicaciones como los sistemas de recomendación, la traducción de idiomas, las redes sociales, los chatbots, la corrección ortográfica, etc. Sin embargo, a menudo se critica a estas redes por ser 'cajas negras', lo que suscita dudas sobre su explicabilidad, especialmente en ámbitos sensibles como la sanidad, la conducción autónoma, etc. Los métodos existentes para mejorar la explicabilidad, como la importancia de las características, suelen carecer de claridad e interpretabilidad. Para solucionar este problema, se ha desarrollado la red neuronal orientada a objetos para mejorar la explicabilidad (OONNIE). OONNIE utiliza el modelado orientado a objetos para combinar la pérdida y el peso de la conexión para calcular la importancia de las características e integra reglas específicas del dominio gracias a la capacidad de ampliación de la programación orientada a objetos. El modelo enfatiza la transparencia algorítmica detallando cada paso del entrenamiento. Evaluado con funciones XOR y XNOR, OONNIE muestra resultados prometedores en la importancia de las características, una reducción más rápida de las pérdidas y una mejora de las predicciones tras integrar reglas de dominio. Esto supone una importante contribución a la IA explicable, lo que convierte a OONNIE en una valiosa herramienta para desarrollar sistemas de IA fiables.…