Extreme Learning Machine for Online Data Classification (Paperback)
Idioma: inglés
Editorial: Nala Kala, 2026
- Tapa blanda
- Nuevo
Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Vendedor de IberLibro desde 22 de junio de 2007
Condición: Nuevo
EUR 39,97
Cantidad disponible: 1 disponible
Añadir al carritoDescripción del artículo del vendedor
Paperback. Extreme Learning Machine for Online Data Classification provides an accessible introduction to the principles, algorithms, and practical concepts behind Extreme Learning Machine (ELM) for online data classification. As machine learning applications increasingly rely on continuously generated data streams, efficient learning methods capable of rapid training and accurate classification have become essential. This book examines how Extreme Learning Machine techniques address these challenges through fast learning algorithms designed for dynamic and evolving datasets.The book introduces the theoretical foundations of Extreme Learning Machine before exploring its role in online learning environments where data arrives continuously and models must adapt efficiently. It discusses the characteristics of online data classification, the importance of computational efficiency, and the practical considerations involved in developing scalable machine learning systems. Readers are introduced to concepts related to incremental learning, adaptive classification, and the performance characteristics that distinguish ELM from many traditional machine learning methods.Designed for engineering and computer science audiences, the book presents machine learning concepts in a structured and organized manner suitable for academic study, professional reference, and self-learning. The material emphasizes the relationship between learning algorithms, computational performance, and classification accuracy while providing a clear overview of Extreme Learning Machine methodologies used for processing continuously evolving datasets.The discussion also places Extreme Learning Machine within the broader field of artificial intelligence and data mining, highlighting its relevance for intelligent systems that require fast model training and efficient prediction. The content serves as a useful resource for understanding the theoretical principles that support modern online classification techniques while maintaining a practical engineering perspective.Suitable for undergraduate and graduate students, researchers, instructors, software engineers, data scientists, and professionals interested in machine learning, this book offers a concise reference to the concepts, terminology, and methodologies associated with Extreme Learning Machine for online data classification. Its focus on computational efficiency, adaptive learning, and intelligent classification makes it valuable for readers seeking a practical understanding of fast machine learning algorithms and their role in modern data-driven applications. This book introduces Extreme Learning Machine (ELM) techniques for online data classification, covering the theoretical foundations, learning algorithms, computational efficiency, and practical machine learning concepts. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…
N° de ref. del artículo 9798349529542
- Título
- Extreme Learning Machine for Online Data Classification (Paperback)
- Autor
- Nitin Verma
- Editorial
- Nala Kala
- Año de publicación
- 2026
- Estado
- new
- Encuadernación
- Paperback
- Idioma
- inglés
- ISBN 13
- 9798349529542
Extreme Learning Machine for Online Data Classification provides an accessible introduction to the principles, algorithms, and practical concepts behind Extreme Learning Machine (ELM) for online data classification. As machine learning applications increasingly rely on continuously generated data streams, efficient learning methods capable of rapid training and accurate classification have become essential. This book examines how Extreme Learning Machine techniques address these challenges through fast learning algorithms designed for dynamic and evolving datasets.
The book introduces the theoretical foundations of Extreme Learning Machine before exploring its role in online learning environments where data arrives continuously and models must adapt efficiently. It discusses the characteristics of online data classification, the importance of computational efficiency, and the practical considerations involved in developing scalable machine learning systems. Readers are introduced to concepts related to incremental learning, adaptive classification, and the performance characteristics that distinguish ELM from many traditional machine learning methods.
Designed for engineering and computer science audiences, the book presents machine learning concepts in a structured and organized manner suitable for academic study, professional reference, and self-learning. The material emphasizes the relationship between learning algorithms, computational performance, and classification accuracy while providing a clear overview of Extreme Learning Machine methodologies used for processing continuously evolving datasets.
The discussion also places Extreme Learning Machine within the broader field of artificial intelligence and data mining, highlighting its relevance for intelligent systems that require fast model training and efficient prediction. The content serves as a useful resource for understanding the theoretical principles that support modern online classification techniques while maintaining a practical engineering perspective.
Suitable for undergraduate and graduate students, researchers, instructors, software engineers, data scientists, and professionals interested in machine learning, this book offers a concise reference to the concepts, terminology, and methodologies associated with Extreme Learning Machine for online data classification. Its focus on computational efficiency, adaptive learning, and intelligent classification makes it valuable for readers seeking a practical understanding of fast machine learning algorithms and their role in modern data-driven applications.
“Sinopsis” puede pertenecer a otra edición de este título.
AussieBookSeller
Truganina, VIC, Australia
Vendedor de IberLibro desde 22 de junio de 2007
Tarifas de envío de Australia a Estados Unidos de America
| Artículo | De 25 a 45 días hábiles | De 8 a 14 días hábiles |
|---|---|---|
| Primer artículo | EUR 33,00 | EUR 39,24 |
Métodos de pago
Información empresarial del vendedor
The Nile Group Pty Ltd
42 Apex Drive
Truganina, VIC Australia 3029
Condiciones de venta
We guarantee the condition of every book as it's described on the Abebooks web sites. If you're dissatisfied with your purchase (Incorrect Book/Not as Described/Damaged) or if the order hasn't arrived, you're eligible for a refund within 30 days of the estimated delivery date. If you've changed your mind about a book that you've ordered, please use the Ask bookseller a question link to contact us and we'll respond within 2 business days.
Derecho al desistimiento
Si es un consumidor, puede rescindir el contrato de acuerdo con lo siguiente. Por consumidor se entiende cualquier persona física que actúe con fines ajenos a su actividad comercial, empresarial, oficio o profesión.
Información sobre el derecho de desistimiento
Derecho legal de desistimiento
Tiene derecho a rescindir este contrato en un plazo de 14 días sin dar ningún motivo.
El periodo de desistimiento vencerá a los 14 días desde que usted, o un tercero que no sea el transportista e indicado por usted, adquiera la posesión física del último bien o del último lote o pieza.
Para ejercer el derecho de desistimiento, complete de forma electrónica y envíe una declaración clara en nuestro sitio web, desde "Mis compras" en "Mi cuenta". Le enviaremos sin demora un acuse de recibo de dicho desistimiento a través de un soporte duradero (por ejemplo, por correo electrónico).
Para cumplir con el plazo de desistimiento, basta con que envíe su comunicación relativa al ejercicio del derecho de desistimiento antes de que venza el periodo de desistimiento.
Efectos del desistimiento
Si rescinde este contrato, le reembolsaremos todos los pagos que hayamos recibido de usted, incluidos los gastos de envío (excepto los gastos adicionales que surjan si elige un tipo de envío que no sea el tipo de envío estándar más económico que ofrecemos).
Podemos hacer una deducción del reembolso por la pérdida de valor de cualquier bien suministrado, si la pérdida es el resultado de una manipulación innecesaria por su parte.
Efectuaremos el reembolso sin demoras indebidas y, a más tardar, 14 días después de que se nos informe de su decisión de rescindir este contrato.
Efectuaremos el reembolso utilizando el mismo medio de pago que utilizó para la transacción inicial, a menos que haya acordado expresamente lo contrario; en cualquier caso, no incurrirá en ningún cargo como resultado de dicho reembolso.
Podremos retener el reembolso hasta que hayamos recibido los bienes o hasta que nos haya presentado una prueba de que los ha devuelto, lo que ocurra primero.
Deberá devolver los bienes o entregarlos a AussieBookSeller, Truganina, Victoria, Australia, sin demoras indebidas y, en cualquier caso, en un plazo máximo de 14 días a partir del día en que nos comunique su desistimiento del presente contrato. El plazo se cumple si devuelve la mercancía antes de que venza el periodo de 14 días. Tendrá que asumir los gastos directos de devolución de los bienes. Usted solo es responsable de la disminución del valor de los bienes como resultado de una manipulación distinta a la necesaria para establecer la naturaleza, las características y el funcionamiento de los bienes.
Excepciones al derecho de desistimiento
El derecho de desistimiento no se aplica a lo siguiente:
- La entrega de periódicos, diarios o revistas, con la excepción de los contratos de suscripción; y
- El suministro de contenido digital que no se proporcione en un soporte tangible (por ejemplo, en un CD o DVD) si, al hacer el pedido, aceptó que podíamos empezar a entregarlo y que no podría desistir una vez iniciada la entrega.
Condiciones de envío
Please note that titles are dispatched from our UK and NZ warehouse. Delivery times specified in shipping terms. Orders ship within 2 business days. Delivery to your door then takes 8-15 days.