Results 191 to 200 of about 23,894,114 (248)

Machine Learning Classification of Prostate Cancer Genomic Sequences Using K-Mer and Sequence-Derived Features. [PDF]

Comput Mol Biosci
Rawat K, Banerjee HN, Noble J, Deloatch SN, Banerjee S, Shetty S, Banerjee S.   +6 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

A New Association Rule-Based Text Classifier Algorithm

17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05), 2005
This paper proposes a new association rule-based text classifier algorithm to improve the prediction accuracy of association rule-based classifier by categories (ARC-BC) algorithm. Unlike the previous algorithms, the proposed association rule generation algorithm constructs two types of frequent itemsets. The first frequent itemsets, i.e.
Supaporn Buddeewong, Worapoj Kreesuradej
exaly   +3 more sources

SYMBIOTIC EVOLUTION OF RULE BASED CLASSIFIER SYSTEMS

International Journal on Artificial Intelligence Tools, 2009
Evolutionary Algorithms are vastly used in development of rule based classifier systems in data mining where the rule base is usually a set of If-Then rules and an evolutionary trait develops and optimizes these rules. Genetic Algorithm is usually a favorite solution for such tasks as it globally searches for good rule-sets without any prior bias or ...
Ramin Halavati, Saeed Bagheri Shouraki, Sima Lotfi, Pooya Esfandiar   +3 more
openaire   +2 more sources

A Possibilistic Rule-Based Classifier

2012
Rule induction algorithms have gained a high popularity among machine learning techniques due to the “intelligibility” of their output, when compared to other “black-box” classification methods. However, they suffer from two main drawbacks when classifying test examples: i) the multiple classification problem when many rules cover an example and are ...
Myriam Bounhas, Henri Prade, Mathieu Serrurier, Khaled Mellouli   +3 more
openaire   +2 more sources

Compact fuzzy association rule-based classifier

Expert Systems with Applications, 2008
Classification is one of the most popular data mining techniques applied to many scientific and industrial problems. The efficiency of a classification model is evaluated by two parameters, namely the accuracy and the interpretability of the model. While most of the existing methods claim their accurate superiority over others, their models are usually
Ferenc Peter Pach, Attila Gyenesei, János Abonyi   +2 more
openaire   +2 more sources

Providing PRTools with fuzzy rule-based classifiers

International Conference on Fuzzy Systems, 2010
This paper first reviews the state-of-the-art of fuzzy rule-based classifiers (FRBCs), then it discusses how to implement an FRBC under the Pattern Recognition Toolbox (PRTools), the de-facto standard toolbox for classification in Matlab. Such an implementation, called frbc, allows for a straightforward comparison of frbc with other classifiers already
COCOCCIONI, MARCO, D'ANDREA, ELEONORA, LAZZERINI, BEATRICE   +2 more
openaire   +2 more sources

Classification Confidence Of Fuzzy Rule-Based Classifiers

ECMS 2011 Proceedings edited by: T. Burczynski, J. Kolodziej, A. Byrski, M. Carvalho, 2011
In this paper we first introduce the concept of classification confidence in fuzzy rule-based classification. Classification confidence shows the strength of classification for an unseen pattern. Low classification confidence for an unseen pattern means that the classification of that pattern is not very clear compared to that with high classification ...
Tomoharu Nakashima, Ashish Ghosh
openaire   +1 more source