/Python/Multinomial regression scikit learn

Multinomial regression scikit learn

model1 = LogisticRegression(random_state=0, multi_class='multinomial', penalty='none', solver='newton-cg').fit(X_train, y_train)
preds = model1.predict(X_test)

#print the tunable parameters (They were not tuned in this example, everything kept as default)
params = model1.get_params()
print(params)

{'C': 1.0, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': None, 'penalty': 'none', 'random_state': 0, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}

Source: datasklr.com

Similar codes

9 votes91 views6 answers
Lists in python
Python
11 votes116 views3 answers
Django q filter
Python
0 vote107 views1 answer
How to get latitude and longitude from address in python
Python
3 votes104 views3 answers
How to take matrix input in python
Python
79 votes103 views6 answers
How to create a virtual environment in python 3
Python
0 vote95 views1 answer
Get index of max value python numpy
Python
2 votes101 views1 answer
Add whitespaces between char python
Python
0 vote94 views1 answer
Python sort by value first then key lexicography
Python
16 votes108 views5 answers
How to create window in tkinter
Python
2 votes105 views1 answer
Native bold text
Python