Arrhythmia is a health problem and it is a drastic cause for many kinds of heart diseases. Some arrhythmia may even cause to death. The main objective of this work is to combine the decision of each classifier in an efficient way to improve the classification accuracy of the classifiers to predict the disease. As different classifiers provide different opinion to the target system, the combined...

In many sport competitions athletes, teams, or countries are evaluated based on several variables. The strong assumptions underlying traditional 'linear weight' scoring systems (that the relative importance, interactions and linearizing transformations of the variables are known) can often not be justified on theoretical grounds, and empirical 'validation' of weights, interactions and transform...

Most machine learning tasks involve learning from high-dimensional data, which is often quite difficult to handle. Hubness is an aspect of the curse of dimensionality that was shown to be highly detrimental to k-nearest neighbor methods in high-dimensional feature spaces. Hubs, very frequent nearest neighbors, emerge as centers of influence within the data and often act as semantic singularitie...

The voter model is one of the standard interacting particle systems. Two related problems for this process are to analyze its behavior, after large times t, for the sets of sites (a) sharing the same opinion as the site 0, and (b) having the opinion that was originally at 0. Results on the sizes of these sets were given in [Sa79] and [BG80]. Here, we investigate the spatial structure of these s...

Classification of spatial data has become important due to the fact that there are huge volumes of spatial data now available holding a wealth of valuable information. In this paper we consider the classification of spatial data streams, where the training dataset changes often. New training data arrive continuously and are added to the training set. For these types of data streams, building a ...

Classification of spatial data has become important due to the fact that there are huge volumes of spatial data now available holding a wealth of valuable information. In this paper we consider the classification of spatial data streams, where the training dataset changes often. New training data arrive continuously and are added to the training set. For these types of data streams, building a ...

Pada akhir 2019 muncul penyakit semacam flu yang menginfeksi paru-paru di kota Wuhan. Diduga tersebut diduga berasal dari kelelawar. WHO memberi nama ini dengan Covid-19 dan virus tersebar ke seluruh dunia sehingga menyebabkan pandemi. Pemerintah mengambil indakan vaksinasi untuk mengatasi ini, namun mendapat respon pro kontra masyarakat. Ada banyak penelitian membahas sentimen masyarakat terha...

Data Envelopment Analysis (DEA) technique now widely use for efficiency evaluation of a set of Decision Making Units (DMUs). As regards of the necessity for ranking efficient units different DEA models presented each of which has advantages and rank efficient units from special aspects. Note that all the existing ranking models have disadvantages, as well and there is not a model in which all t...