PySIPS
User Guide
Quickstart Guide
Installation
Basic Usage
Expected Output
Understanding the Parameters
Accessing Results
Next Steps
Common Issues
PySIPS Tutorial
Table of Contents
1. Basic Symbolic Regression
2. Multivariate Regression
3. Customizing Available Operators
Available operators:
4. Model Selection Strategies
5. Checkpointing for Long Runs
6. Hyperparameter Tuning
7. Analyzing the Posterior Distribution
Advanced Topics
Mutation and Crossover Control
Expression Complexity Control
SMC Sampling Control
Best Practices
Troubleshooting
Issue: Fitting is too slow
Issue: Poor model quality
Issue: Overfitting
Issue: Checkpoint file corrupted
Further Resources
API Reference
PySIPS API Documentation
API Reference
Main Components
PysipsRegressor
Core Modules
Sampler
Prior
Metropolis
Laplace NMLL
Proposal Mechanisms
Mutation Proposal
Crossover Proposal
Random Choice Proposal
Quick Links
PySIPS
Index
Index
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C
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E
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F
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G
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L
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M
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P
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R
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S
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U
_
__call__() (pysips.crossover_proposal.CrossoverProposal method)
(pysips.laplace_nmll.LaplaceNmll method)
(pysips.mutation_proposal.MutationProposal method)
(pysips.random_choice_proposal.RandomChoiceProposal method)
__init__() (pysips.crossover_proposal.CrossoverProposal method)
(pysips.laplace_nmll.LaplaceNmll method)
(pysips.metropolis.Metropolis method)
(pysips.mutation_proposal.MutationProposal method)
(pysips.prior.Prior method)
(pysips.PysipsRegressor method)
(pysips.random_choice_proposal.RandomChoiceProposal method)
__init_subclass__() (pysips.PysipsRegressor class method)
C
CrossoverProposal (class in pysips.crossover_proposal)
E
evaluate_log_likelihood() (pysips.metropolis.Metropolis method)
evaluate_log_priors() (pysips.metropolis.Metropolis method)
evaluate_model() (pysips.metropolis.Metropolis method)
F
fit() (pysips.PysipsRegressor method)
G
get_expression() (pysips.PysipsRegressor method)
get_metadata_routing() (pysips.PysipsRegressor method)
get_models() (pysips.PysipsRegressor method)
get_params() (pysips.PysipsRegressor method)
L
LaplaceNmll (class in pysips.laplace_nmll)
M
Metropolis (class in pysips.metropolis)
module
pysips.crossover_proposal
pysips.laplace_nmll
pysips.metropolis
pysips.mutation_proposal
pysips.prior
pysips.random_choice_proposal
pysips.sampler
MutationProposal (class in pysips.mutation_proposal)
P
predict() (pysips.PysipsRegressor method)
Prior (class in pysips.prior)
pysips.crossover_proposal
module
pysips.laplace_nmll
module
pysips.metropolis
module
pysips.mutation_proposal
module
pysips.prior
module
pysips.random_choice_proposal
module
pysips.sampler
module
PysipsRegressor (class in pysips)
R
RandomChoiceProposal (class in pysips.random_choice_proposal)
run_smc() (in module pysips.sampler)
rvs() (pysips.prior.Prior method)
S
sample() (in module pysips.sampler)
score() (pysips.PysipsRegressor method)
set_params() (pysips.PysipsRegressor method)
set_score_request() (pysips.PysipsRegressor method)
smc_metropolis() (pysips.metropolis.Metropolis method)
U
update() (pysips.crossover_proposal.CrossoverProposal method)
(pysips.mutation_proposal.MutationProposal method)
(pysips.random_choice_proposal.RandomChoiceProposal method)