PAKDD
2010
ACM
14 years 4 months ago
2010
ACM
Abstract. Mining of data streams must balance three evaluation dimensions: accuracy, time and memory. Excellent accuracy on data streams has been obtained with Naive Bayes Hoeffdi...
CICLING
2004
Springer
14 years 5 months ago
2004
Springer
When text categorization is applied to complex tasks, it is tedious and expensive to hand-label the large amounts of training data necessary for good performance. In this paper, we...
CEAS
2005
Springer
14 years 5 months ago
2005
Springer
This paper explores the use of the naive Bayes classifier as the basis for personalised spam filters. Several machine learning algorithms, including variants of naive Bayes, hav...
AI
2005
Springer
14 years 5 months ago
2005
Springer
The instance-based k-nearest neighbor algorithm (KNN)[1] is an effective classification model. Its classification is simply based on a vote within the neighborhood, consisting o...
ADMA
2005
Springer
14 years 5 months ago
2005
Springer
Accurate probability-based ranking of instances is crucial in many real-world data mining applications. KNN (k-nearest neighbor) [1] has been intensively studied as an effective c...
ADMA
2005
Springer
14 years 5 months ago
2005
Springer
In real-world data mining applications, an accurate ranking is same important to a accurate classification. Naive Bayes (simply NB) has been widely used in data mining as a simple...
DASFAA
2005
IEEE
14 years 5 months ago
2005
IEEE
Naive Bayes has been widely used in data mining as a simple and effective classification algorithm. Since its conditional independence assumption is rarely true, numerous algorit...
ICPR
2010
IEEE
14 years 5 months ago
2010
IEEE
—Randomized learning methods (i.e., Forests or Ferns) have shown excellent capabilities for various computer vision applications. However, it was shown that the tree structure in...
FSKD
2007
Springer
14 years 5 months ago
2007
Springer
Naïve Bayes is a well-known effective and efficient classification algorithm, but its probability estimation performance is poor. Averaged One-Dependence Estimators, simply AODE,...
ECML
2007
Springer
14 years 5 months ago
2007
Springer
Averaged One-Dependence Estimators (AODE) classifies by uniformly aggregating all qualified one-dependence estimators (ODEs). Its capacity to significantly improve naive Bayes...