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We study random connections with different probability distributions.
In this study random forests once more proved to solve predictive chemoinformatic modelling tasks best.
In a carefully designed and implemented experimental study, random assignment of treatment overcomes the selection bias.
In this study, random individuals were sampled and showed excessive body fat depositions (unpubl. observation).
In this study, random subsampling is conducted to train and evaluate classifiers.
In this study, random fabric layers with an embedded core distribution medium is used.
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We also study random-walk-type processes constructed from DNA sequences, and find that the eigenvalue spectrum from PCA of those random-walk processes also follow power-law relations, with the exponent characterizing the correlation structures of the DNA sequence.
We also study random-restart GD to optimize the transcription rate model.
Due to cluster-sampling of school units in the study, random-effects and between school variance were estimated by means of Mixed Linear Models [ 42].
Many scholars have studied random infectious disease models [13 20].
Numerical approximation is still an interesting method for studying random periodicity in random dynamical systems.
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