How can I access "Log" in pipelines?

pipelines = {"Log": Pipeline([("scl", StandardScaler()), ("est", LogisticRegression(random_state=1))]),"Rf": Pipeline([("est", RandomForestClassifier(random_state=1))]),"Rf_Pipeline": Pipeline([("scl", StandardScaler()),("reduct", PCA(n_components=10, random_state=1)),("est", RandomForestClassifier(random_state=1)),]),
}Pipelines.item(Log)

Currently I get:

NameError: name 'Log' is not defined

The pipeline objects can be viewed as dictionaries. In your case, you have stored multiple pipelines into a dictionary. To access the different keys (pipelines) you can simply use dict['key'] or dict.get['key'].

1. For the first level (sub pipelines), simply use dict['key']
2. For the second level, (steps inside sub pipelines), again, you can fetch the dict with steps using named_steps and then refer to each step the same way.

Here is a the code -

from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.linear_model import LogisticRegression
from sklearn.decomposition import PCA
from sklearn.ensemble import RandomForestClassifierpipelines = {"Log": Pipeline([("scl", StandardScaler()), ("est", LogisticRegression(random_state=1))]),"Rf": Pipeline([("est", RandomForestClassifier(random_state=1))]),"Rf_Pipeline": Pipeline([("scl", StandardScaler()),("reduct", PCA(n_components=10, random_state=1)),("est", RandomForestClassifier(random_state=1)),]),
}first_subpipeline = pipelines['Log']
second_step_first_subpipeline =  pipelines['Log'].named_steps['est']print(first_subpipeline)
print(second_step_first_subpipeline)

Pipeline(steps=[('scl', StandardScaler()),('est', LogisticRegression(random_state=1))])LogisticRegression(random_state=1)