· Boosting1 IntroductionThe purpose of supervised learning is to classify patterns (also known as instances) into aset of categories which are also referred to as classes or labels. Commonly, the classificationis based on a classification models (classifiers) that are induced from an exemplary set...
Ensemble of classifiersSupervised learningClassificationBoostingThe idea of ensemble methodology is to build a predictive model by integrating multiple models. It is well-known that ensemble methods can be used for improving prediction performance. Researchers from various disciplines such as statistics and ...
2.1 静态选择方法(只选择基学习器的一个子集,缺乏灵活性) 2.1.1 ordering-based methods 基于某些准则对基学习器进行排序,然后选择排序较高的。具体方法有:validation error , kappa measure , complementary measure 和 margin。 2.2.2 optimization-based methods 1)启发式方法:演化算法 2)数学规划方法:二次整数规...
Ensemble-based Classifiers for Cancer Classification Using Human Tumor Microarray Data In this paper, two cancer classification techniques based on multicategory microarray data sets are presented. Due to the high dimensionality of microarray... A Margoosian,J Abouei - Electrical Engineering 被引量: ...
A classifier may be regarded as a computer based agent, which can perform a classification task. Classifiers can be divided into two categories [3]: rule-based classifiers and soft computing based classifiers. Rule-based classifiers are generally constructed by the designer, where the designer defin...
GOSS(Gradient-based One-Side Sampling,单边梯度采样)的目标是在减少训练样本降低计算复杂度的同时又保持算法的精度。 简单来说,GOSS的做法是保留了所有大梯度的样本,随机选取小梯度的样本用于训练。为了避免这样做对原始数据分布产生较大改变,又对小梯度样本乘以一个因子\frac{1-a}{b}进行了缩放,其中a是对样本按...
However, instead of using the same training set to fit the individual classifiers in the ensemble, we draw bootstrap samples (random samples with replacement) from the initial training set, which is why bagging is also known asbootstrap aggregating. To provide a more concrete example of how bo...
However, instead of using the same training set to fit the individual classifiers in the ensemble, we draw bootstrap samples (random samples with replacement) from the initial training set, which is why bagging is also known asbootstrap aggregating. To provide a more concrete example of how bo...
Intrusion detection method based on ensemble learning is studied by using multiple classifiers. 利用多分类器技术,研究了基于集成学习的入侵检测方法. 期刊摘选 His professional career began in 1960 when he joined L . A . R & B ensemble the Upfronts. 1960年,他加入了洛杉矶R & B合唱团“前沿”,开...
EEG-based motor imagery classification using wavelet coefficients and ensemble classifiers Brain-computer interface (BCI) is a system that captures and decodes electroencephalogram (EEG) signals and transforms human thoughts into actions. To achi... R Ebrahimpour,K Babakhani,M Mohammad-Noori - IEEE ...