This paper deals with the problem of feature subset selection in classification oriented datasets with a (very) large number of attributes. In such datasets the classical wrapper approaches become intractable due to the high number of wrapper evaluations to be carried out. One way to alleviate this problem is to use the so-called filter-wrapper approach, which consists in the construction of a ...

Semi-automatic wrapper generation tools aim to ease the task of building structured views over web sources. But the wrapper generation techniques presented up to date show several weaknesses when dealing with the complex commercial web sources of today, specially when constructing advanced navigational sequences for accessing data. We present Wargo, a semi-automatic wrapper generation tool, whi...

The proliferation of online information sources has accentuated the need for tools that automatically validate and recognize data. We present an efficient algorithm that learns structural information about data from positive examples alone. We describe two Web wrapper maintenance applications that employ this algorithm. The first application detects when a wrapper is not extracting correct data...

The premise, upon which I evaluate the TCP-friendliness of VOIP traffic, is content and the necessary justification. In the reminder of this paper I will give a description of the paper as well as the assumptions and claims of the authors. Also I will give my own personal conclusions about the authors’ work along with sufficient justifications.

Different approaches have been proposed for feature selection to obtain suitable features subset among all features. These methods search feature space for feature subsets which satisfies some criteria or optimizes several objective functions. The objective functions are divided into two main groups: filter and wrapper methods.  In filter methods, features subsets are selected due to some measu...

Predicting stock prices is an important objective in the financial world. This paper presents a novel forecasting model for stock markets on the basis of the wrapper ANFIS (Adaptive Neural Fuzzy Inference System)ICA (Imperialist Competitive Algorithm) and technical analysis of Japanese Candlestick. Two approaches of Raw-based and Signal-based are devised to extract the model’s input variables w...

This paper deals with the problem of feature subset selection in classification-oriented datasets with a (very) large number of attributes. In such datasets complex classical wrapper approaches become intractable due to the high number of wrapper evaluations to be carried out. One way to alleviate this problem is to use the so-called filter-wrapper approach or Incremental Wrapper-based Subset S...

Instance selection methods are very useful data mining tools for dealing with large data sets. There exist many instance selection algorithms capable for significant reduction of training data size for particular classifier without generalization degradation. In opposition to those methods, this paper focuses on general pruning methods which can be successfully applied for arbitrary classificat...