Description:
greentsetlin 1.0.1
Green Tsetlin
Installation
Green Tsetlin can be installed by the following:
pip install green-tsetlin
Tsetlin Machine
The Tsetlin Machine is the core of Green Tsetlin.
import green_tsetlin as gt
tm = gt.TsetlinMachine(n_literals=4,
n_clauses=5,
n_classes=2,
s=3.0,
threshold=42,
literal_budget=4,
boost_true_positives=False,
multi_label=False)
Trainer
Green Tsetlin Trainer is a simple wrapper for the Tsetlin Machine.
import green_tsetlin as gt
tm = gt.TsetlinMachine(n_literals=4,
n_clauses=5,
n_classes=2,
s=3.0,
threshold=42,
literal_budget=4)
trainer = gt.Trainer(tm, seed=42, n_jobs=2)
trainer.set_train_data(train_x, train_y)
trainer.set_eval_data(eval_x, eval_y)
trainer.train()
Exporting Tsetlin Machines
Exporting trained Tsetlin Machines.
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tm.save_state("tsetlin_state.npz")
Loading exported Tsetlin Machines
Loading trained Tsetlin Machines to continue training or use for inference.
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tm.load_state("tsetlin_state.npz")
Inference
Inference with trained Tsetlin Machines.
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predictor = tm.get_predictor()
predictor.predict(x)
Green Tsetlin hpsearch
With the built-in hyperparameter search you can optimize your Tsetlin Machine parameters.
from green_tsetlin.hpsearch import HyperparameterSearch
hyperparam_search = HyperparameterSearch(s_space=(2.0, 20.0),
clause_space=(5, 10),
threshold_space=(3, 20),
max_epoch_per_trial=20,
literal_budget=(1, train_x.shape[1]),
seed=42,
n_jobs=5,
k_folds=4,
minimize_literal_budget=False)
hyperparam_search.set_train_data(train_x, train_y)
hyperparam_search.set_eval_data(test_x, test_y)
hyperparam_search.optimize(trials=10)
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
Customer Reviews
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