Search alternatives:
forest classification » text classification (Expand Search), risk classification (Expand Search), disease classification (Expand Search)
data optimization » path optimization (Expand Search), dose optimization (Expand Search), art optimization (Expand Search)
class forest » across forest (Expand Search), tasc forest (Expand Search)
class data » claims data (Expand Search)
forest classification » text classification (Expand Search), risk classification (Expand Search), disease classification (Expand Search)
data optimization » path optimization (Expand Search), dose optimization (Expand Search), art optimization (Expand Search)
class forest » across forest (Expand Search), tasc forest (Expand Search)
class data » claims data (Expand Search)
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The statistical description of the original data set of the patients (<i>n</i> = 162).
Published 2025Subjects: -
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The list of parameters of the modified data set for machine learning (<i>n</i> = 162).
Published 2025Subjects: -
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<i>hi</i>PRS algorithm process flow.
Published 2023“…<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>. …”
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ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction.
Published 2025Subjects: -
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The comparison of the accuracy score of the benchmark and the proposed models.
Published 2025Subjects: -
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Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%).
Published 2025Subjects: -
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Calibration curve of the ABC–LR–RF hybrid model for IVF outcome prediction.
Published 2025Subjects: -
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Correlation matrix of all twelve features.
Published 2025“…Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. …”
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Model 3: Biomarkers only.
Published 2025“…Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. …”