A parabolic relationship between prediction errors and learning rates obtained by a cubic learning algorithm. by Boluwatife Ikwunne (22238697)

The algorithm for the same-day surgery protocol. by Magnus Tveit (11442200)

Probability density of the cumulative number <i>C</i> of infections for different system sizes <i>N</i> at their critical vaccination doses with the random vaccination strategy as... by Yannick Feld (16520678)

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Cleavage time as a function of scaled fiber diameter. by Roukayatou R. Ouedraogo (20460980)

Rate functions Φ(<i>C</i>) for the random vaccination heuristics for different system sizes <i>N</i> at their respective critical vaccination. by Yannick Feld (16520678)

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Multimodal reference functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Affiliation function of unwinding tension deviation bias <i>e</i>. by Yanjun Xiao (1993411)

Affiliation function of polar slice correction bias <i>e</i>. by Yanjun Xiao (1993411)

Test functions. by Kejia Liu (5699651)

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The convergence curves of the test functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Single-peaked reference functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

AP improvement rates for various targets on the RSOD dataset. by Pingping Yan (462509)

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Identifying cognitive impairment with story recall (Wilson et al., 2024) by Sarah C. Wilson (19370966)

“…Discourse data were used to classify participants testing within range of cognitive impairment using multiple machine learning algorithms and stability analysis for identifying reliably predictive features in an effort to maximize prediction accuracy. …”

Probability density functions of the cumulative fraction <i>C</i> of infections for <i>N</i> = 3200 for the different vaccination strategies. by Yannick Feld (16520678)

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AP improvement rates for various targets on the NWPU VHR-10 dataset. by Pingping Yan (462509)

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Probability density functions of the cumulative fraction <i>C</i> of infected nodes for <i>N</i> = 3200 for the different vaccination strategies. by Yannick Feld (16520678)

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Test results of multimodal benchmark functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Fixed-dimensional multimodal reference functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Test results of multimodal benchmark functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Wav2DDK: An automated DDK estimation algorithm (Kadambi et al., 2023) by Prad Kadambi (16680635)

“…Estimated rates achieve a high test-retest reliability (<em>r</em> = .95) and show good correlation with the revised ALS functional rating scale speech subscore (<em>r </em>= .67).…”