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Found 4 papers, 0 papers with code
Enabling clustering algorithms to detect clusters of varying densities through scale-invariant data preprocessing
In this paper, we show that preprocessing data using a variant of rank transformation called 'Average Rank over an Ensemble of Sub-samples (ARES)' makes clustering algorithms robust to data representation and enable them to detect varying density clusters.
Requirements Engineering Framework for Human-centered Artificial Intelligence Software Systems
[Method] In this paper, we present a new framework developed based on human-centered AI guidelines and a user survey to aid in collecting requirements for human-centered AI-based software.
A Novel Data Pre-processing Technique: Making Data Mining Robust to Different Units and Scales of Measurement
In this paper, we present a better and effective alternative based on ranks over multiple sub-samples of data.
Improved histogram-based anomaly detector with the extended principal component features
In this era of big data, databases are growing rapidly in terms of the number of records.
