We present a novel method that aims at providing a more stable selection of feature subsets when variations in the training process occur. This is accomplished by using an instance-weighting process –assigning different importances to instances– as a preprocessing step to a feature weighting method that is independent of the learner, and then making good use of both sets of computed weigths in ...

In this paper, an innovative data pre-processing method to improve the classification performance and to determine automatically the vertebral column disorders including disk hernia (DH), spondylolisthesis (SL) and normal (NO) groups has been proposed. In the classification of vertebral column disorders' dataset with three classes, a pairwise fuzzy C-means (FCM) based feature weighting method h...

Community detection is one of the primary problems in social network analysis and this problem has more challenges attributed networks. The purpose community networks to discover communities with not only homogeneous node properties but also adherent structures. Although been extensively studied, large a number attributes remains vital challenge. To address challenge, paper novel method develop...

BACKGROUND Similarity-based retrieval of Electronic Health Records (EHRs) from large clinical information systems provides physicians the evidence support in making diagnoses or referring examinations for the suspected cases. Clinical Terms in EHRs represent high-level conceptual information and the similarity measure established based on these terms reflects the chance of inter-patient disease...

This paper presents INTIMATE, a web-based movie recommender that makes suggestions by using text categorization to learn from movie synopses The performance of various feature representations, feature selectors, feature weighting mechanisms and classifiers is evaluated and discussed. INTIMATE was also compared with a feature-based movie recommender. The results show that the text-based approach...

We describe a sequential universal data compression procedure for binary tree sources that performs the " double mixture. " Using a context tree, this method weights in an efficient recursive way the coding distributions corresponding to all bounded memory tree sources, and achieves a desirable coding distribution for tree sources with an unknown model and unknown parameters. Computational and ...

In this paper, a sub-vector weighting scheme is proposed for the case of small sample in image retrieval with relevance feedback. By partitioning a multi-dimensional visual feature vector to multiple sub-vectors, the singularity problem caused by small sample can be avoided by the lower dimensionality of the sub-vectors. Then the optimal weighting can be performed on these sub-vectors respectiv...

Drought directly affects environmental sustainability. Predicting the drought at earliest opportunity will help to execute mitigation plans. Several indices are used predict severity of across different geographical regions. The two main in India for meteorological standardized precipitation index (SPI) and evapotranspiration (SPEI). This work is a study find ability above mentioned state Tamil...