Extreme Gradient Boosting for Data Mining Applications

Name: Extreme Gradient Boosting for Data Mining Applications
Brand: LAP Lambert Academic Publishing
SKU: 9786138236122
Price: 33.05 EUR
Availability: InStock

Автор: Nonita Sharma

Език:

Корици: С меки корици

Издател: LAP Lambert Academic Publishing

Наличност: Външен склад

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Prediction models have reached to a stage where a single model is not sufficient to make predictions...

Информация за книгата

Автор

Nonita Sharma

Език

Английски език

Корици

Книга - С меки корици

Издадена

2018

страници

EAN

9786138236122

Enbook ID

19346006

Издател

LAP Lambert Academic Publishing

Теглоt

113

Размери

150 x 220 x 4

Пълно описание

Prediction models have reached to a stage where a single model is not sufficient to make predictions. Hence, to achieve better accuracy and performance, an ensemble of various models are being used. Gradient Boosting Algorithm has almost been the part of all ensembles. Winners of Kaggle Competition are swearing by this. Extreme Gradient Boosting is a step forward to this where we try to optimise the loss function. In this research work Squared Logistic Loss function is used with Boosting function which is expected to reduce bias and variance. The proposed model is applied on stock market data for the past ten years. Squared Logistic Loss function with XGBoost promises to be an effective approach in terms of accuracy and better prediction.

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Extreme Gradient Boosting for Data Mining Applications

Информация за книгата

Пълно описание

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