Data classification plays important role in the field of data mining. The increasing rate of data diversity and size decrease the performance and efficiency of classifier. The decreasing performance of classifier compromised with unvoted data of classifier. Now the merging of two or more classifier for better prediction and voting of data are used, such techniques are called Ensemble classifier...

Abstract We present the first version of Automatic Learning for Rapid Classification Events (ALeRCE) broker light curve classifier. ALeRCE is currently processing Zwicky Transient Facility (ZTF) alert stream, in preparation Vera C. Rubin Observatory. The classifier uses variability features computed from ZTF stream and colors obtained AllWISE photometry. apply a balanced random forest algorithm...

This paper considers the generation of some interpretable fuzzy rules for assigning an amino acid sequence into the appropriate protein superfamily. Since the main objective of this classifier is the interpretability of rules, we have used the distribution of amino acids in the sequences of proteins as features. These features are the occurrence probabilities of six exchange groups in the seque...

In this paper we present a new classifier based on sequential classification rules for protein localization prediction. We also present three compact representations for encoding, in a concise form, the knowledge available in a classification rule set. Experiments run on the Gram-bacteria data set show that the classifier achieves both high prediction and good recall. Furthermore, since rules c...

Hyperspectral image classification plays a vital role in today’s era. Identifying the suitable classifier and dimensionality reduction method is a chronic task for the Hyperspectral Image Classification on par with high accuracy and reliability. Image classification using multiple classifier system has been said to be evolving method for improving the accuracy and the reliability. The problems ...

Error-Correcting Output Coding (ECOC) is a general framework for multiclass text classification with a set of binary classifiers. It can not only help a binary classifier solve multi-class classification problems, but also boost the performance of a multi-class classifier. When building each individual binary classifier in ECOC, multiple classes are randomly grouped into two disjoint groups: po...

land cover is one of basic data layers in geographic information system for physical planning and environmentalmonitoring. digital image classification is generally performed to produce land cover maps from remote sensing data,particularly for large areas. in the present study the multispectral image from irs liss-iii image along with ancillary datasuch as vegetation indices, principal componen...