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r-lib
generics:Common S3 Generics not Provided by Base R Methods Related to Model Fitting
In order to reduce potential package dependencies and conflicts, generics provides a number of commonly used S3 generics.
Maintained by Hadley Wickham. Last updated 1 years ago.
61 stars 14.00 score 131 scripts 9.8k dependentstidymodels
baguette:Efficient Model Functions for Bagging
Tree- and rule-based models can be bagged (<doi:10.1007/BF00058655>) using this package and their predictions equations are stored in an efficient format to reduce the model objects size and speed.
Maintained by Max Kuhn. Last updated 2 months ago.
25 stars 8.13 score 624 scripts 1 dependentsjonathan-g
datafsm:Estimating Finite State Machine Models from Data
Automatic generation of finite state machine models of dynamic decision-making that both have strong predictive power and are interpretable in human terms. We use an efficient model representation and a genetic algorithm-based estimation process to generate simple deterministic approximations that explain most of the structure of complex stochastic processes. We have applied the software to empirical data, and demonstrated it's ability to recover known data-generating processes by simulating data with agent-based models and correctly deriving the underlying decision models for multiple agent models and degrees of stochasticity.
Maintained by Jonathan M. Gilligan. Last updated 4 years ago.
11 stars 5.52 score 30 scriptsbioc
HPiP:Host-Pathogen Interaction Prediction
HPiP (Host-Pathogen Interaction Prediction) uses an ensemble learning algorithm for prediction of host-pathogen protein-protein interactions (HP-PPIs) using structural and physicochemical descriptors computed from amino acid-composition of host and pathogen proteins.The proposed package can effectively address data shortages and data unavailability for HP-PPI network reconstructions. Moreover, establishing computational frameworks in that regard will reveal mechanistic insights into infectious diseases and suggest potential HP-PPI targets, thus narrowing down the range of possible candidates for subsequent wet-lab experimental validations.
Maintained by Matineh Rahmatbakhsh. Last updated 5 months ago.
proteomicssystemsbiologynetworkinferencestructuralpredictiongenepredictionnetwork
3 stars 4.95 score 6 scripts