منابع مشابه
Boosting Support Vector Machines
This paper presents a classification algorithm based on Support Vector Machines classifiers combined with Boosting techniques. This classifier presents a better performance in training time, a similar generalization and a similar model complexity but the model representation is more compact.
متن کاملGradient boosting machines, a tutorial
Gradient boosting machines are a family of powerful machine-learning techniques that have shown considerable success in a wide range of practical applications. They are highly customizable to the particular needs of the application, like being learned with respect to different loss functions. This article gives a tutorial introduction into the methodology of gradient boosting methods with a str...
متن کاملSupport Vector Machines versus Boosting
Support Vector Machines (SVMs) and Adaptive Boosting (AdaBoost) are two successful classification methods. They are essentially the same as they both try to maximize the minimal margin on a training set. In this work, we present an even platform to compare these two learning algorithms in terms of their test error, margin distribution and generalization power. Two basic models of polynomials an...
متن کاملTransformation Equivariant Boltzmann Machines
We develop a novel modeling framework for Boltzmann machines, augmenting each hidden unit with a latent transformation assignment variable which describes the selection of the transformed view of the canonical connection weights associated with the unit. This enables the inferences of the model to transform in response to transformed input data in a stable and predictable way, and avoids learni...
متن کاملGEFCom2012 Hierarchical load forecasting: Gradient boosting machines and Gaussian processes
This report discusses methods for forecasting hourly loads of a US utility as part of the load forecasting track of the Global Energy Forecasting Competition 2012 hosted on Kaggle. The methods described (gradient boosting machines and Gaussian processes) are generic machine learning / regression algorithms and few domain specific adjustments were made. Despite this, the algorithms were able to ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistics and Computing
سال: 2019
ISSN: 0960-3174,1573-1375
DOI: 10.1007/s11222-019-09870-4