作者：
Madhu, G.Rajinikanth, T. V.VNR VJIET
Dept Informat Technol Hyderabad 500090 Andhra Pradesh India GRIET
Dept Informat Technol Hyderabad 500085 Andhra Pradesh India
The problem of missing data in the real world datasets has very significant role in the real time datamining process and becomes more complex in large databases. The presence of missing values influences data set fea...
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ISBN:
(纸本)9781467324816;9781467313445
The problem of missing data in the real world datasets has very significant role in the real time datamining process and becomes more complex in large databases. The presence of missing values influences data set features and the class attributes, thus affecting the predictive accuracies of the classifiers. For the last one decade, many researchers have come out with different techniques for dealing with missing attribute values in databases with homogeneous and/or numeric attributes. In this research work, we proposed a new indexing measure to the imputation algorithm for missing data values of the attributes to compute the similarity measure between any two typical elements in the dataset. It can also be applied on any dataset be it a nominal and/or real. The proposed algorithm is evaluated by extensive experiments and comparison with KNNI, SVMI, WKNNI, KMI and FKMI algorithms. The results showed that the proposed algorithm has better performance than the existing imputation algorithms in terms of classification accuracy and also our decision tree algorithm employs highly accurate decision rules.
A new method for dimensionality reduction and feature extraction based on Support Vector machines and minimization of the within-class data dispersion is proposed. An iterative procedure is proposed that successively ...
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Place recognition is important navigation ability for autonomous navigation of mobile robots. Visual cues extracted from images provide a way to represent and recognize visited places. In this article, a multi-cue bas...
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In recent years, improvement in ubiquitous technologies and sensor networks have motivated the application of datamining techniques to network organized data. Network data describe entities represented by nodes, whic...
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Regression is the study of functional dependency of one numeric variable with respect to another. In this paper, we present a novel, efficient, binary search based regression algorithm having the advantage of low comp...
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The quality of extracted features is the key issue to text mining due to the large number of terms, phrases, and noise. Most existing text mining methods are based on term-based approaches which extract terms from a t...
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MultiVoxel pattern Analysis (MVPA) is presented as a successful alternative to the General Linear Model (GLM) for fMRI data analysis. We report different experiments using MVPA to master several key parameters. We fou...
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data stream is one emerging topic of datamining, it concerns many applications involving large and temporal data sets such as telephone records data, banking data, multimedia data,... For mining of such data, one cru...
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Software defect detection has been an important topic of research in the field of software engineering for more than a decade. This research work aims to evaluate the performance of supervised machinelearning techniq...
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The proceedings contain 230 papers. The topics discussed include: WIPOMTS: an Internet public opinion monitoring system;social context enabled description model for web services;improved learning algorithm for self-ad...
ISBN:
(纸本)9783642340406
The proceedings contain 230 papers. The topics discussed include: WIPOMTS: an Internet public opinion monitoring system;social context enabled description model for web services;improved learning algorithm for self-adaptive neural nets based on principal component analysis;digital library network based on the san technology;research of a vertical search engine for campus network;efficient control scheme for surface temperature of hot roller based on neural network;adaptivity in location-based services;an evolution model of emotional Internet public opinion with informed marks;support vector machine classification algorithm and its application;a flatness patternrecognition model based on wavelet transform and probabilistic neural network;research on reduction algorithm based on variable precision rough set;and a modified group search optimizer algorithm for high dimensional function optimization.
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