A Bayesian Committee Machine

ارتقای کیفیت دسته‌بندی متون با استفاده از کمیته‌ دسته‌بند دو سطحی

Nowadays, the automated text classification has witnessed special importance due to the increasing availability of documents in digital form and ensuing need to organize them. Although this problem is in the Information Retrieval (IR) field, the dominant approach is based on machine learning techniques. Approaches based on classifier committees have shown a better performance than the others. I...

A Bayesian Committee Machine

Transductive and Inductive Methods for Approximate Gaussian Process Regression

Gaussian process regression allows a simple analytical treatment of exact Bayesian inference and has been found to provide good performance, yet scales badly with the number of training data. In this paper we compare experimentally three of the leading approaches towards scaling Gaussian processes regression to large data sets: the subset of representers method, the reduced rank approximation, ...

The Bayesian Committee Support Vector Machine

Empirical evidence indicates that the training time for the support vector machine (SVM) scales to the square of the number of training data points. In this paper, we introduce the Bayesian committee support vector machine (BC-SVM) and achieve an algorithm for training the SVM which scales linearly in the number of training data points. We verify the good performance of the BC-SVM using several...

Committee Machines

In this chapter, we describe some of the most important architectures and algorithms for committee machines. We discuss three reasons for using committee machines. The first reason is that a committee can achieve a test set performance unobtainable by a single committee member. As typical representative approaches, we describe simple averaging, bagging and boosting. Secondly with committee mach...

Naive Bayesian Classiier Committees

The naive Bayesian classiier provides a very simple yet surprisingly accurate technique for machine learning. Some researchers have examined extensions to the naive Bayesian classiier that seek to further improve the accuracy. For example, a naive Bayesian tree approach generates a decision tree with one naive Bayesian classiier at each leaf. Another example is a constructive Bayesian classiier...