Normal view MARC view ISBD view

Unsupervised and semi-supervised clustering algorithms for outliers detection in high dimensional data : M.Phil Statistics

Material type: materialTypeLabel

BookPublisher: Islamabad: AIOU, 2019Description: xiv, 115p.Subject(s): Cluster analysis- Data processing

Tags from this library: No tags from this library for this title. Add tag(s)

average rating: 0.0 (0 votes)

No physical items for this record

Previous	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	Next
Previous	519.5095491492 NAI Identification of the risk factors of prostate cancer in Faisalabad (Pakistan)	519.52 SAE Empirical comparison of some well known estimators in two Phase sampling	519.53 QUM Monitoring the product and process quality of linear profile under the Non-Parametric control designs	519.53 SAU Unsupervised and semi-supervised clustering algorithms for outliers detection in high dimensional data	519.535 SAP The preferences of news channels through paired comparisons model under bayesian Framework	519.536 Construction of control charts using regression models with correlated regressors	519.536 ANV Variable selection via scad-penalized quantile regression for high-dimensional count data	Next

Eng

There are no comments for this item.

AIOU Library