Research on transform of outliers based on density

This paper proposed a data transform method based on error-adjusted density of micro-datasets, so as to distinguish the characteristics of outliers efficiently and improve the accuracy of prediction models. It divided the large multi-dimensional data sets into many grid cells, and in each cell assig...

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Bibliographic Details
Main Authors: Ge Xin, Ding Enjie
Format: Conference Proceeding
Language:English
Subjects:
Data Transform
Density Estimation
Micro-Dataset
Outlier
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Summary:This paper proposed a data transform method based on error-adjusted density of micro-datasets, so as to distinguish the characteristics of outliers efficiently and improve the accuracy of prediction models. It divided the large multi-dimensional data sets into many grid cells, and in each cell assigned each data point to its closest micro-dataset using a nearest neighbor algorithm, data points were represented by calculating the error-adjusted density estimation in each micro-dataset. Thereby, the processed data could embody the information of the area which they belonged to and show the data variation characteristics rightly.
ISSN:1948-9439
1948-9447
DOI:10.1109/CCDC.2008.4597421