Post-processing of classifier outputs in multiple classifier systems

Altincay, H
Demirekler, Mübeccel
Incomparability in classifier outputs due to the variability in their scales is a major problem in the combination of different classification systems. In order to compensate this, output normalization is generally performed where the main aim is to transform the outputs onto the same scale. In this paper, it is proposed that in selecting the transformation function, the scale similarity goal should be accomplished with two more requirements. The first one is the separability of the pattern classes in the transformed output space and the second is the compatibility of the outputs with the combination rule. A method of transformation that provides improved satisfaction of the additional requirements is proposed which is shown to improve the classification performance of both linear and Bayesian combination systems based on the use of confusion matrix based a posteriori probabilities....


Undesirable effects of output normalization in multiple classifier systems
Altincay, H; Demirekler, Mübeccel (Elsevier BV, 2003-06-01)
Incomparability of the classifier output scores is a major problem in the combination of different classification systems. In order to deal with this problem, the measurement level classifier outputs are generally normalized. However, empirical results have shown that output normalization may lead to some undesirable effects. This paper presents analyses for some most frequently used normalization methods and it is shown that the main reason for these undesirable effects of output normalization is the dimen...
Classification via ensembles of basic thresholding classifiers
TOKSÖZ, Mehmet Altan; Ulusoy, İlkay (Institution of Engineering and Technology (IET), 2016-08-01)
The authors present a sparsity-based algorithm, basic thresholding classifier (BTC), for classification applications which is capable of identifying test samples extremely rapidly and performing high classification accuracy. They introduce a sufficient identification condition (SIC) under which BTC can identify any test sample in the range space of a given dictionary. By using SIC, they develop a procedure which provides a guidance for the selection of threshold parameter. By exploiting rapid classification...
Estimation of pico-satellite attitude dynamics and external torques via Unscented Kalman Filter
Söken, Halil Ersin (FapUNIFESP (SciELO), 2014-01-01)
In this study, an Unscented Kalman Filter (UKF) algorithm is designed for estimating the attitude of a picosatellite and the in-orbit external disturbance torques. The estimation vector is formed by the satellite's attitude, angular rates, and the unknown constant components of the external disturbance torques acting on the satellite. The gravity gradient torque, residual magnetic moment, sun radiation pressure and aerodynamic drag are all included in the estimated external disturbance torque vector. The sa...
Genome-wide exploration of metal tolerance protein (MTP) genes in common wheat (Triticum aestivum): insights into metal homeostasis and biofortification
Vatansever, Recep; Filiz, Ertugrul; Eroğlu, Seçkin (2017-04-01)
Metal transport process in plants is a determinant of quality and quantity of the harvest. Although it is among the most important of staple crops, knowledge about genes that encode for membrane-bound metal transporters is scarce in wheat. Metal tolerance proteins (MTPs) are involved in trace metal homeostasis at the sub-cellular level, usually by providing metal efflux out of the cytosol. Here, by using various bioinformatics approaches, genes that encode for MTPs in the hexaploid wheat genome (Triticum ae...
Input variable selection for hydrological predictions in ungauged catchments: with or without clustering
Doğulu, Nilay; Batmaz, İnci; Kentel Erdoğan, Elçin (null; 2018-04-08)
A key step in data-driven environmental modelling, including for hydrological purposes, is input variable selection (IVS) to ensure that the least number of variables with minimum redundancy are used to characterize the inherent relationship between inputs and outputs. Hydrological predictions in ungauged catchments is one such area where the information on influential predictors of runoff signatures guides in understanding dominant controls of meaningful information transfer from gauged to ungauged locatio...
Citation Formats
H. Altincay and M. Demirekler, “Post-processing of classifier outputs in multiple classifier systems,” MULTIPLE CLASSIFIER SYSTEMS, pp. 159–168, 2002, Accessed: 00, 2020. [Online]. Available: