data-specific preprocessing methods
A Comprehensive Survey on Data Preprocessing Methods in Web Usage Minning
... application specific methodology for preprocessing the web log data and a modified frequent pattern tree for discovery of pattern ...log preprocessing, rather than traditional approach, which ...
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eUTOPIA: solUTion for Omics data PreprocessIng and Analysis
... contrast specific coefficients from the original coefficients of the linear ...specifying methods “ Holm ” , “ Hochberg ”, “Hommel”, “Bonferroni”, “Benjamini & Hochberg”, “Benjamini and Yekutieli” or ...
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Statistical learning methods as a preprocessing step for survival analysis: evaluation of concept using lung cancer data
... SL methods with epidemiologic analyses was ...this data, the hybrid approach provided greater Az in the logistic regression modeling and greater hazard relationships in the survival analyses than that of ...
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Comparing different data preprocessing methods for monitoring soil heavy metals based on soil spectral features
... the data (Chu et ...scaling methods, SNV is a widely used technique, especially in NIR applications, which corrects the multiplicative interferences of light scatter and par- ticle size by centering and ...
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Preprocessing differential methylation hybridization microarray data
... microarray data obtained from two-color cDNA microarray and single-color Affymetrix array have been extensively studied ...that preprocessing methods for microarrays are platform specific and ...
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Preprocessing on bilingual data for Statistical Machine Translation
... CRFs are conditional probabilistic models not unlike HMMs for labeling or segmenting sequential data, such as a plaintext corpus. One of the problems with labeling sequential data is that the data ...
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ASAP: an environment for automated preprocessing of sequencing data
... sequencing data so that researchers can quickly start their statistical analyses as well as incrementally add new data as is often necessary for large-scale research pro- ...for preprocessing human ...
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Big data preprocessing: methods and prospects
... used data preprocessing techniques. It transforms quantitative data into qualitative data by dividing the numerical features into a limited number of non- overlapped ...Any data mining ...
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MeteoIO 2.4.2: a preprocessing library for meteorological data
... Meteorological data processing benchmarks Reading meteorological data stored in an ASCII file bears a significant ...spective data types and the data need to be stored in mem- ory for further ...
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AN EFFICIENT CONTENT BASED DATA CLUSTERING AND PREPROCESSING FOR BIG DATA
... Big Data revolution, and proposes a Big Data processing model, from the data mining ...This data-driven model involves demand-driven aggregation of information sources, mining and analysis, ...
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Ensembles of First Order Logical Decision Trees for Imbalanced Classification Problems
... learning methods [5], [6]. Although these methods do somewhat alleviate the problem, they are often based on heuristics rather than on clear ...across data sets, and is usually determined through ...
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Lung Nodule Detection
... Preprocessing is the method of resizing the image into a number of small patches. The aim of preprocessing is an improvement of the image data that suppresses unwanted distortion or enhances some ...
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Applications of Rough Sets Theory in Data Preprocessing for Knowledge Discovery
... original data To evaluate the effect of the algorithm, we compute the misclassification error after and before instance ...only data discretized by rough sets and Chi-Merge ...
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Combined gene selection methods for microarray data analysis
... ranking methods col- lected by Cho and Won [3], namely Signal-to-Noise ratio (SN), correlation co- efficient (CC), Euclidean (EU) and Cosine (CO) ranking ...these methods are intuitive, simple and easy to ...
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Combined gene selection methods for microarray data analysis
... Considering of wrapper methods: SVMs and C4.5 are not only benchmark clas- sification systems, but each of them contains a wrapper gene selection method. SVMs uses a recursive feature elimination(RFE) approach to ...
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DPASF: a flink library for streaming data preprocessing
... The first layer receives the sequence of input data and the range of the variable and keeps some statistics on the data using many more intervals than required. The range of the variable is used to ...
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Are Cry Studies Replicable? An Analysis of Participants, Procedures, and Methods Adopted and Reported in Studies of Infant Cries
... the methods and data analysis sections of their papers, researchers are consistent in reporting the software and hardware used in their work (even though the software version or hardware version was ...
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Data Preprocessing and Easy Access Retrieval of Data through Data Ware House
... However, data preprocessing has received far less attention than it ...deserves. Methods for user identification, session zing, and path completion, are presented in ...several data ...
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An Enhanced Methods of Preprocessing in Web Log Mining
... web data volume, and the dynamic property of information source, it is extremely difficult to find out the useful information from the ...etc. Data preprocessing is the primary and principle step, ...
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To Predict Rain Fall in Desert Area of Rajasthan Using Data Mining Techniques
... monsoon-rainfall data series is highly complex and the multiple linear regressions might play a vital role for the future ...Rajasthan) data set which is derived using correlation analysis and regression ...
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