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Ensemble Machine Learning: Methods and Applications ebook

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It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed "ensemble learning" by researchers in computational intelligence and machine learning, it is known to improve a decision system's robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as "boosting" and "random forest" facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics.Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.Product details Publisher: Springer; 2012 edition (February 17, 2012) Publication Date: February 17, 2012

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It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics.Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.Product details Publisher: Springer; 2012 edition (February 17, 2012) Publication Date: February 17, 2012

Ensemble Machine Learning: Methods and Applications ebook

$28.00

It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed?ensemble learning? by researchers in computational intelligence and machine learning, it is known to improve a decision system?s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as?boosting? and?random forest? facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.Additional ISBNs9781489988171Ensemble Machine Learning: Methods and Applications is written by Cha Zhang and published by Springer. ISBNs for Ensemble Machine Learning are 9781441993267, 1441993266 and the print ISBNs are 9781441993250, 1441993258. Additional ISBNs include 9781489988171.

Order Processing Time

Shipping Methods and Carriers

Zetlly partners exclusively with reputable shipping carriers to ensure timely delivery of your orders. We utilize:

FedEx
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USPS

The choice of carrier is determined by factors such as destination, weight, and delivery timeframe to provide optimal service.

Shipping Rates and Fees

Free shipping is provided for all orders over $199.
Orders under $199 will incur a flat-rate shipping fee of $7.99.
All orders shipped within the United States will be subject to a sales tax charge of 5%.

Estimated Delivery Time

Shipping Restrictions

Tracking Your Order

Please allow up to 48 hours for tracking information to update in the carrier’s system.

Eligibility for Returns and Exchanges

How to Return or Exchange an Item

To initiate a return or exchange, please follow these steps:

Contact our customer support at [email protected] with your order number and reason for return or exchange.
Our team will respond within 24 hours to provide detailed instructions, including the specific Return Address for your shipment.
Package your item securely and include all original packaging and proof of purchase.

Return shipments should be sent to: Blanq LLC 1201 South Hope Street Apt 2413, Los Angeles, CA 90015, USA

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Items must be returned in their original condition, unworn, undamaged, and complete with all original packaging and documentation.
Items returned without prior authorization or not meeting the above conditions may not qualify for a refund or exchange.

Return Shipping Costs

Non-Returnable Items

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Digital products (e-books or downloadable content)
Personalized or customized items
Gift cards

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Payment Security

Zetlly does not store any credit card or sensitive financial information directly on our servers, further enhancing the security and protection of your personal data.