Deep Learning

Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form

Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form a strong classifier. Adaptive Boosting (Adaboost) implements this idea as a greedy search for a linear combination of classifiers by overweighting the examples that are misclassified by each classifier. icsiboost implements Adaboost over stumps (one-level decision trees) on discrete and continuous attributes (words and real values). See http://en.wikipedia.org/wiki/AdaBoost and the papers by Y. Freund and R. Schapire for more details [1]. This approach is one of most efficient and simple to combine continuous and nominal values. Our implementation is aimed at allowing training from millions of examples by hundreds of features in a reasonable time/memory.

标签： meta-learning classifiers combining Boosting

上传时间： 2016-01-30

上传用户：songnanhua
主要是KNN（the k-nearest neighbor　algorithm ）,LVQ1（learning vector quantization 1）, DSM（decision surface

主要是KNN（the k-nearest neighbor　algorithm ）,LVQ1（learning vector quantization 1）, DSM（decision surface mapping）算法。 and a simple clustering algorithm.

标签： quantization k-nearest algorithm decision

上传时间： 2016-02-07

上传用户：zhyiroy
LabVIEW7实用教程 learning 全部资料完整版

LabVIEW7实用教程 learning 全部资料完整版

标签： LabVIEW7 learning 实用教程

上传时间： 2016-02-09

上传用户：gmh1314
Learning Multi-scale Block Local Binary Patterns for Face Recognition”

Learning Multi-scale Block Local Binary Patterns for Face Recognition”

标签： Multi-scale Recognition Learning Patterns

上传时间： 2016-02-11

上传用户：cursor
Reinforcement Learning

Reinforcement Learning

标签： Reinforcement Learning

上传时间： 2016-02-13

上传用户：WMC_geophy
Parking Lot Simulation： Parking lot attendants often park cars bumper-to-bumper, several cars deep.

Parking Lot Simulation： Parking lot attendants often park cars bumper-to-bumper, several cars deep. This maximizes the number of cars they can fit into a parking lot at the expense of complicating the process of retrieving someone s car when they want to leave. Consider the case of a person wanting to leave the parking lot but their car is parked in the back of a row of cars. In this case, all the cars parked in front of this person s car must be temporarily moved to allow this person to leave.

标签： Parking cars bumper-to-bumper Simulation

上传时间： 2016-02-15

上传用户：lepoke
SpikeLM: A Second-Order Supervised Learning Algorithm for Training Spiking Neural Networks Introduc

SpikeLM: A Second-Order Supervised Learning Algorithm for Training Spiking Neural Networks Introduction Preliminaries SpikeLM algorithm Experimental validation Conclusions

标签： Second-Order Supervised Algorithm Learning

上传时间： 2014-01-13

上传用户：zhuimenghuadie
Labview国际象棋,it is useful if you are learning labview

Labview国际象棋,it is useful if you are learning labview

标签： learning Labview labview useful

上传时间： 2013-12-17

上传用户：zsjzc
This book is finite element method learning book.

This book is finite element method learning book.

标签： book learning element finite

上传时间： 2016-02-19

上传用户：784533221
新神经网络 Extreme Learning Machine 比SVM快

新神经网络 Extreme Learning Machine 比SVM快，附4个例子

标签： Learning Extreme Machine SVM

上传时间： 2013-12-27

上传用户：水中浮云