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Data pre-processing

Known as: Data preprocessing 
Data pre-processing is an important step in the data mining process. The phrase "garbage in, garbage out" is particularly applicable to data mining… 
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Related topics

Related topics

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Data miningData qualityFeature extractionFeature selection

Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2011
2011
Implementation of Data Mining Techniques for Meteorological Data Analysis (A case study for Gaza Strip)
Meteorological data mining is a form of data mining concerned with finding hidden patterns inside largely available… 
2011
2011
A Novel Technique for Web Log mining with Better Data Cleaning and Transaction Identification
Problem statement: In the internet era web sites on the internet are useful source of information for almost every activity. So… 
2010
2010
Feature Extraction for Characterization of Breast Lesions in Ultrasound Echography and Elastography
Problem statement: Elastography is developed as a quantitative approach to imaging linear elastic properties of tissues to detect… 
2009
2009
Research on Web Session Clustering
The task of clustering web sessions is to group web sessions based on similarity and consists of maximizing the intra-group… 
2008
2008
Pixel Level Fusion of Panchromatic and Multispectral Images Based on Correspondence Analysis
A pixel level data fusion approach based on correspondence analysis (CA) is introduced for high spatial and spectral resolution… 
2007
2007
Scientific programming with Java classes supported with a scripting interpreter
jLab environment provides a Matlab/Scilab like scripting language that is executed by an interpreter, implemented in the Java… 
2006
2006
A Multiple Neural Network System to Classify Solder Joints on Integrated Circuits
The following paper introduces a diagnostic process to detect solder joint defects on Printed Circuit Boards assembled in Surface… 
2006
2006
Modeling Meteorological Prediction Using Particle Swarm Optimization and Neural Network Ensemble
In this paper a novel optimization approach is presented. Network architecture and connection weights of neural networks (NN) are… 
2004
2004
Nearest-Neighbours for Time Series
This paper presents an application of lazy learning algorithms in the domain of industrial processes. These processes are… 
1994
1994
Nonlinear Hebbian rule: a statistical interpretation
Recently, the extension of Hebbian learning to nonlinear units has received increased attention. Some successful applications of…