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fix: issue of running automl in SVM and Decision Tree #429

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fix: issue of running automl in SVM and Decision Tree #429

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10 changes: 8 additions & 2 deletions geochemistrypi/data_mining/model/regression.py
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Original file line number Diff line number Diff line change
Expand Up @@ -920,7 +920,10 @@ def __init__(self, task="regression", n_jobs=None, **config):
@classmethod
def search_space(cls, data_size, task):
space = {
"criterion": {"domain": tune.choice(["squared_error", "friedman_mse", "absolute_error", "poisson"])},
# "criterion": {"domain": tune.choice(["squared_error", "friedman_mse", "absolute_error", "poisson"])},
# TODO: Handle the issue of 'poisson' not supporting negative values. This workaround excludes 'poisson' for now.
# Future work: If required, implement a solution to support negative values for 'poisson' or handle them dynamically.
"criterion": {"domain": tune.choice(["squared_error", "friedman_mse", "absolute_error"])},
"max_depth": {"domain": tune.randint(lower=2, upper=20), "init_value": 1, "low_cost_init_value": 1},
"min_samples_split": {
"domain": tune.randint(lower=2, upper=10),
Expand Down Expand Up @@ -1738,7 +1741,10 @@ def __init__(self, task="regression", n_jobs=None, **config):
def search_space(cls, data_size, task):
space = {
"C": {"domain": tune.uniform(lower=1, upper=data_size[0]), "init_value": 1, "low_cost_init_value": 1},
"kernel": {"domain": tune.choice(["poly", "rbf", "sigmoid"])},
# "kernel": {"domain": tune.choice(["poly", "rbf", "sigmoid"])},
# TODO: Exclude 'poly' kernel due to its slow search speed and negative impact on framework performance.
# Future work: Reevaluate kernel options if performance requirements change or improvements are made to handle 'poly' more efficiently.
"kernel": {"domain": tune.choice(["rbf", "sigmoid"])},
"gamma": {"domain": tune.uniform(lower=1e-5, upper=10), "init_value": 1e-1, "low_cost_init_value": 1e-1},
"degree": {"domain": tune.quniform(lower=1, upper=5, q=1), "init_value": 3, "low_cost_init_value": 3},
"coef0": {"domain": tune.uniform(lower=0, upper=1), "init_value": 0, "low_cost_init_value": 0},
Expand Down