rgnoisefilt

Traditional noise filtering methods aim at removing noisy samples from a classification dataset. This package adapts classic and recent filtering techniques for use in regression problems, and it also incorporates methods specifically designed for regression data. In order to do this, it uses approaches proposed in the specialized literature, such as Martin et al. (2021) [doi:10.1109/ACCESS.2021.3123151] and Arnaiz-Gonzalez et al. (2016) [doi:10.1016/j.eswa.2015.12.046]. Thus, the goal of the implemented noise filters is to eliminate samples with noise in regression datasets.

Last 30 days

This package has been downloaded 138 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 4 times.

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Last 365 days

This package has been downloaded 1,965 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Aug 22, 2024 with 20 downloads.

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