linear-tree
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How to gridsearch tree and regression parameters?
Hi, I am wondering how to perform a GridsearchCV to find best parameters for the tree and regression model? For now I am able to tune the tree component of my model:
`
param_grid={
'n_estimators': [50, 100, 500, 700],
'max_depth': [10, 20, 30, 50],
'min_samples_split' : [2, 4, 8, 16, 32],
'max_features' : ['sqrt', 'log2', None]
}
cv = RepeatedKFold(n_repeats=3,
n_splits=3,
random_state=1)
model = GridSearchCV(
LinearForestRegressor(ElasticNet(random_state = 0), random_state=42),
param_grid=param_grid,
n_jobs=-1,
cv=cv,
scoring='neg_root_mean_squared_error'
)
`