Discriminant Parameter Learning of Belief Net Classifiers
نویسنده
چکیده
منابع مشابه
Adaptive Learning Rate for Online Linear Discriminant Classifiers
We propose a strategy for updating the learning rate parameter of online linear classifiers for streaming data with concept drift. The change in the learning rate is guided by the change in a running estimate of the classification error. In addition, we propose an online version of the standard linear discriminant classifier (O-LDC) in which the inverse of the common covariance matrix is update...
متن کاملComparison of 14 different families of classification algorithms on 115 binary datasets
We tested 14 very different classification algorithms (random forest, gradient boosting machines, SVM linear, polynomial, and RBF 1-hidden-layer neural nets, extreme learning machines, k-nearest neighbors and a bagging of knn, naive Bayes, learning vector quantization, elastic net logistic regression, sparse linear discriminant analysis, and a boosting of linear classifiers) on 115 real life bi...
متن کاملLearning Bayesian Belief Network Classifiers: Algorithms and System
This paper investigates the methods for learning Bayesian belief network (BN) based predictive models for classification. Our primary interests are in the unrestricted Bayesian network and Bayesian multi-net based classifiers. We present our algorithms for learning these classifiers and also the methods for fighting the overfitting problem. A natural method for feature subset selection is also ...
متن کاملA Multichannel Deep Belief Network for the Classification of EEG Data
Deep learning, and in particular Deep Belief Network (DBN), has recently witnessed increased attention from researchers as a new classification platform. It has been successfully applied to a number of classification problems, such as image classification, speech recognition and natural language processing. However, deep learning has not been fully explored in electroencephalogram (EEG) classif...
متن کاملPinpointing the classifiers of English language writing ability: A discriminant function analysis approach
The major aim of this paper was to investigate the validity of language and intelligence factors for classifying Iranian English learners` writing performance. Iranian participants of the study took three tests for grammar, breadth, and depth of vocabulary, and two tests for verbal and narrative intelligence. They also produced a corpus of argumentative writ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2001