Feature reduction set

Attribute reduction is one important part researched in rough set theory. A reduct from a decision table is a minimal subset of the conditional attributes which provide the same information for classification purposes as the entire set of available attributes.

16p vimulcahy 18-09-2023 3 2   Download

We develop a New Keynesian model featuring Calvo price setting and Calvo wage setting to study welfare consequences of exogenous variations in trend inflation. We find that shifting trend inflation produces a large welfare cost, which can be mainly accounted not only by a reduction of the average level of consumption and working hours, but also by an increase in their volatility.

15p vihassoplattner 07-01-2022 20 1   Download

A set of catalysts having gold nanoparticles deposited on γ-Al2O3 (Au/γ-Al2O3) with lowest effective amount of gold content were prepared by successive impregnation and hydrogen reduction method. The structural features of prepared catalysts were analysed by X-ray diffraction (XRD), N2 physisorption, scanning electron microscopy (SEM), and Fourier transform infrared (FTIR). The catalytic activity was evaluated for the reduction of an organic pollutant 4-nitrophenol (4NP) to 4-aminophenol (4AP) by spectrophotometric analysis.

13p tudichquannguyet 29-11-2021 9 1   Download

Gene set scoring provides a useful approach for quantifying concordance between sample transcriptomes and selected molecular signatures. Most methods use information from all samples to score an individual sample, leading to unstable scores in small data sets and introducing biases from sample composition (e.g. varying numbers of samples for different cancer subtypes).

10p vicoachella2711 27-10-2020 8 1   Download

The paper aims to improve the multi-label classification performance using the feature reduction technique. According to the determination of the dependency among features based on fuzzy rough relation, features with the highest dependency score will be retained in the reduction set.

8p tamynhan4 06-09-2020 4 1   Download

The development of the Internet has increased the need for daily online information storage. Finding the correct information that we are interested in takes a lot of time, so the use of techniques for organizing and processing text data are needed. These techniques are called text classification or text categorization. There are many methods of text classification, but for this paper we study and apply the Support Vector Machine (SVM) method and compare its effect with the Naïve Bayes probability method.

17p caothientrangnguyen 01-04-2020 61 1   Download

This system clearly analyzed both destination feature data set and source data set. After so many experiments, we are able to achieve 97% reduction of false alarm rate which significantly improves the efficiency.

11p blossom162 31-03-2019 26 2   Download

We develop a general feature space for automatic classification of verbs into lexical semantic classes. Previous work was limited in scope by the need for manual selection of discriminating features, through a linguistic analysis of the target verb classes (Merlo and Stevenson, 2001). We instead analyze the classification structure at a higher level, using the possible defining characteristics of classes as the basis for our feature space.

8p bunthai_1 06-05-2013 52 2   Download

In this paper, we propose guided learning, a new learning framework for bidirectional sequence classification. The tasks of learning the order of inference and training the local classifier are dynamically incorporated into a single Perceptron like learning algorithm. We apply this novel learning algorithm to POS tagging. It obtains an error rate of 2.67% on the standard PTB test set, which represents 3.3% relative error reduction over the previous best result on the same data set, while using fewer features. ...

8p hongvang_1 16-04-2013 48 1   Download

In this work, we present a novel approach to the generation task of ordering prenominal modifiers. We take a maximum entropy reranking approach to the problem which admits arbitrary features on a permutation of modifiers, exploiting hundreds of thousands of features in total. We compare our error rates to the state-of-the-art and to a strong Google ngram count baseline. We attain a maximum error reduction of 69.8% and average error reduction across all test sets of 59.1% compared to the state-of-the-art and a maximum error reduction of 68.

8p hongdo_1 12-04-2013 39 3   Download

This work develops and defends a structural view of the nature of mathematics, which is used to explain a number of striking features of mathematics that have puzzled philosophers for centuries. It rejects the most widely held philosophical view of mathematics (Platonism), according to which mathematics is a science dealing with mathematical objects such as sets and numbers—objects which are believed not to exist in the physical world.

394p bimap_5 28-12-2012 46 7   Download