Model.set_params¶

In [ ]:

Model.set_params(parameters: dict = {})

Sets the parameters of the model.

Parameters¶

Name	Type	Optional	Description
parameters	dict	✓	New parameters. This must be a dictionary where the keys and values are Pipeline names and parameters, respectively.

Example¶

In [15]:

from verticapy.learn.preprocessing import StandardScaler
from verticapy.learn.ensemble import RandomForestRegressor
from verticapy.learn.pipeline import Pipeline

model1 = StandardScaler("public.Std_winequality")
model2 = RandomForestRegressor(name = "public.RF_winequality",
                               n_estimators = 20,
                               max_features = "auto",
                               max_leaf_nodes = 32, 
                               sample = 0.7,
                               max_depth = 3,
                               min_samples_leaf = 5,
                               min_info_gain = 0.0,
                               nbins = 32)
model = Pipeline([("WineSTD", model1), ("WineRF", model2)])
model.get_params()

Out[15]:

{'WineRF': {'max_depth': 3,
  'max_features': 'auto',
  'max_leaf_nodes': 32,
  'min_info_gain': 0.0,
  'min_samples_leaf': 5,
  'n_estimators': 20,
  'nbins': 32,
  'sample': 0.7},
 'WineSTD': {'method': 'zscore'}}

In [18]:

model.set_params({"WineRF": {"max_depth": 6}})
model.get_params()

Out[18]:

{'WineRF': {'max_depth': 6,
  'max_features': 'auto',
  'max_leaf_nodes': 32,
  'min_info_gain': 0.0,
  'min_samples_leaf': 5,
  'n_estimators': 20,
  'nbins': 32,
  'sample': 0.7},
 'WineSTD': {'method': 'zscore'}}