Performances of Naïve Bayes (NB), Multilayer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), Support Vector Machine (SVM) and K- Nearest Neighbors (KNN). حسب Solomon Shiferaw Beyene (9143178)

Accuracy, sensitivity, specificity and F-score. حسب Solomon Shiferaw Beyene (9143178)

The figures showed a comparison of the balanced and imbalanced sequences and performance of classifiers. حسب Solomon Shiferaw Beyene (9143178)

Performance comparison of RWDisEnh on the heterogeneous network of diseases and enhancers and that on the enhancer functional interaction network and the disease similarity network... حسب Duc-Hau Le (603529)

Core genes were selected through PPI analysis based on three algorithms. حسب Dong-Hee Han (140305)

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. حسب Gursimran Singh (575288)

الموضوعات:

Distinct microbial and functional composition between age groups. حسب Elio L. Herzog (11576876)

الموضوعات: "…applying independent algorithms…"

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

Summary of results of naïve Bayes algorithms. حسب Christopher E. Niemczak (8586861)

"…<div><p>Importance</p><p>Predicting neurocognitive deficits using complex auditory assessments could change how cognitive dysfunction is identified, and monitored over time. …"

Characteristic chart of algorithm efficiency. حسب Wang Xiaoqian (10502222)

Algorithm test with a 4mm deep. حسب Nicolas Herzig (9230425)

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... حسب Hector Torres (11708207)

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. حسب Gursimran Singh (575288)

الموضوعات:

Cost functions implemented in Neuroptimus. حسب Máté Mohácsi (20469514)

Descriptive statistics of the dataset with mean, standard deviation (SD), median, and the lower (quantile 5%) and upper (quantile 95%) boundary of the 90% confidence interval. حسب Achim Langenbucher (3156741)

الموضوعات:

Optimised formula constants for the SRKT, the Hoffer Q, the Holladay 1, Haigis (with optimised a0 and preset values a1 = 0.4 / a2 = 0.1, Haigis1; and with optimised a0 / a1 / a2 co... حسب Achim Langenbucher (3156741)

الموضوعات:

Cumulative density function (CDF) of prediction error (PE, achieved spherical equivalent–formula predicted spherical equivalent) for the SRKT, Hoffer Q, Holladay1, Haigis (with opt... حسب Achim Langenbucher (3156741)

الموضوعات:

Prediction error (PE) as the difference between achieved and formula predicted spherical equivalent for 8 different statistical metrics of formula constant optimisation and various... حسب Achim Langenbucher (3156741)

الموضوعات:

Dice score for various <i>α</i> values (from the Eq 8) for the tracking of the CST and for the iFOD and PTT algorithms. حسب Thomas Durantel (20933812)

الموضوعات:

Five types of Beta functions considered. حسب Luan Carlos de Sena Monteiro Ozelim (16914117)