Determine the sample size requirement to achieve the target probability of correct classification (PCC) for studies employing high-dimensional features. The package implements functions to 1) determine the asymptotic feasibility of the classification problem; 2) compute the upper bounds of the PCC for any linear classifier; 3) estimate the PCC of three design methods given design assumptions; 4) determine the sample size requirement to achieve the target PCC for three design methods.
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Summary
Determine the sample size requirement to achieve the target probability of correct classification (PCC) for studies employing high-dimensional features. The package implements functions to 1) determine the asymptotic feasibility of the classification problem; 2) compute the upper bounds of the PCC for any linear classifier; 3) estimate the PCC of three design methods given design assumptions; 4) determine the sample size requirement to achieve the target PCC for three design methods.
Last Updated
Jun 27, 2022 at 19:24
License
GPL-2
Total Downloads
110
Supported Platforms