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DDoutlier  

Distance & Density-Based Outlier Detection
View on CRAN: Click here


Download and install DDoutlier package within the R console
Install from CRAN:
install.packages("DDoutlier")

Install from Github:
library("remotes")
install_github("cran/DDoutlier")

Install by package version:
library("remotes")
install_version("DDoutlier", "0.1.0")



Attach the package and use:
library("DDoutlier")
Maintained by
Jacob H. Madsen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-05-30
Latest Update: 2018-05-30
Description:
Outlier detection in multidimensional domains. Implementation of notable distance and density-based outlier algorithms. Allows users to identify local outliers by comparing observations to their nearest neighbors, reverse nearest neighbors, shared neighbors or natural neighbors. For distance-based approaches, see Knorr, M., & Ng, R. T. (1997) , Angiulli, F., & Pizzuti, C. (2002) , Hautamaki, V., & Ismo, K. (2004) and Zhang, K., Hutter, M. & Jin, H. (2009) . For density-based approaches, see Tang, J., Chen, Z., Fu, A. W. C., & Cheung, D. W. (2002) , Jin, W., Tung, A. K. H., Han, J., & Wang, W. (2006) , Schubert, E., Zimek, A. & Kriegel, H-P. (2014) , Latecki, L., Lazarevic, A. & Prokrajac, D. (2007) , Papadimitriou, S., Gibbons, P. B., & Faloutsos, C. (2003) , Breunig, M. M., Kriegel, H.-P., Ng, R. T., & Sander, J. (2000) , Kriegel, H.-P., Kr
How to cite:
Jacob H. Madsen (2018). DDoutlier: Distance & Density-Based Outlier Detection. R package version 0.1.0, https://cran.r-project.org/web/packages/DDoutlier. Accessed 21 Nov. 2024.
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Complete documentation for DDoutlier
Functions, R codes and Examples using the DDoutlier R package
Some associated functions: COF . DB . INFLO . KDEOS . KNN_AGG . KNN_IN . KNN_SUM . LDF . LDOF . LOCI . LOF . LOOP . NAN . NOF . RDOS . RKOF . 
Some associated R codes: OutlierFunctionLibrary.R .  Full DDoutlier package functions and examples
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