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

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Homomorphic binary tree. by Jianhua He (341366)

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

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

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

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

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

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

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

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

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Confusion matrix of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

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

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Flow diagram of the conversion of drugs into active substances. by Uğur Ejder (22683228)

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Calibration curve of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

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

“…<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>. …”

Spontaneous ERG-based random forest model discriminates control and disease cases in rodent models of obesity and type 1 diabetes and predicts disease evolution in the type 1 diabe... by Ramsés Noguez Imm (6658637)

Models and Dataset by M RN (9866504)

“…</p><p dir="ltr"><br></p><p dir="ltr"><b>RAO (Rao Optimization Algorithm):</b><br>RAO is a parameter-less optimization algorithm that updates solutions based on simple arithmetic operations involving the best and worst individuals in the population. …”

Supplementary Material 8 by Nishitha R Kumar (19750617)

“…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…”