<i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

"…<p><b>(A)</b> Input data is a list of genotype-level SNPs. <b>(B)</b> Focusing on the positive class only, the algorithm exploits FIM (<i>apriori</i> algorithm) to build a list of candidate interactions of any desired order, retaining those that have an empirical frequency above a given threshold <i>δ</i>. …"

Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification حسب Vaibhavi Patel (19843282)

CSTP-MAC algorithm backoff time-slots vs IEEE 802.15.4 binary backoff exponential algorithm backoff time-slots. حسب Innocent Uzougbo Onwuegbuzie (9243166)

Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things حسب Ashok Kumar K (21441108)

الموضوعات:

Binary contingency table. حسب Lu Xiao (314030)

Confusion matrix for a binary outcome (adapted from Fawcett [30]). حسب João Albuquerque (12936572)

Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data حسب Changhun Kim (682542)

"…However, ToxCast assays differ in the amount of data and degree of class imbalance (CI). Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. …"

Top-performing model configuration and performance by algorithm type. حسب Uğur Ejder (22683228)

الموضوعات:

Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes حسب Yu Y. (3096192)

"…Our estimate of m is the maximizer of a marginal likelihood obtained by integrating the latent log-ORs out of the joint distribution of the parameters and observed data. We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation. …"

The illustration depicts our CQ-CNN architecture for binary image classification. حسب Mominul Islam (3513758)

The statistical description of the original data set of the patients (<i>n</i> = 162). حسب Uğur Ejder (22683228)

الموضوعات:

The list of parameters of the modified data set for machine learning (<i>n</i> = 162). حسب Uğur Ejder (22683228)

الموضوعات:

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses حسب Meichen Liu (8168148)

ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction. حسب Uğur Ejder (22683228)

الموضوعات:

The accuracy score change matrix following model development. حسب Uğur Ejder (22683228)

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The comparison of the accuracy score of the benchmark and the proposed models. حسب Uğur Ejder (22683228)

الموضوعات:

The prediction accuracy of simple versus hybrid models. حسب Uğur Ejder (22683228)

الموضوعات:

Flow diagram of the proposed model. حسب Uğur Ejder (22683228)

الموضوعات:

Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%). حسب Uğur Ejder (22683228)

الموضوعات:

The most effective active substances for subfertility treatment. حسب Uğur Ejder (22683228)

الموضوعات: