How to tune hyperparameters with grid search using sklearn in Python?

by | Feb 16, 2023 | AI, Machine Learning and Deep Learning, Featured, Machine Learning Using Python, Python Scikit-learn

Hyperparameters are parameters that are passed as arguments to the constructor of the estimator. For example, in Lasso regression, the parameter alpha can be considered as a hyperparameter. We can tune these hyperparameters to optimize the performance of our model.

In grid search, we perform an exhaustive search over specified parameter values of an estimator. For example, in Lasso regression, we can give a set of alpha values and perform an exhaustive search to find out which alpha value gives the optimal result. If there is more than one parameter, then the parameters are specified in a grid, and an exhaustive search is performed for each combination of the parameters to find out the optimal values of the parameters.

In Python, we can use the GridSearchCV() function for grid search parameter tuning. We can use the following Python code to perform a grid search to find out the optimal alpha value for Lasso regression.

import numpy
import seaborn
from sklearn.linear_model import Lasso
from sklearn.model_selection import GridSearchCV

data = seaborn.load_dataset("mpg")
data.dropna(inplace=True)

D = data.values
X = data.drop(labels=["origin", "name", "mpg"], axis=1).values
y = data.filter(items=["mpg"], axis=1).values

alphas = numpy.linspace(0.01, 1, num=100, endpoint=True)
params = dict(alpha=alphas)
regressor = Lasso()
grid_search_cv = GridSearchCV(estimator=regressor, param_grid=params, cv=10, scoring="r2")
grid_search_cv.fit(X, y)

print(grid_search_cv.best_estimator_)
print(grid_search_cv.best_score_)

Here, we are reading the mpg dataset using the seaborn Python library. In this dataset, we are given a set of car models along with their horsepower, weight, acceleration, mpg or miles driven per 1 gallon of gasoline, etc. We want to create a Lasso …

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Amrita Mitra

Author

Ms. Amrita Mitra is an author, who has authored the books “Cryptography And Public Key Infrastructure“, “Web Application Vulnerabilities And Prevention“, “A Guide To Cyber Security” and “Phishing: Detection, Analysis And Prevention“. She is also the founder of Asigosec Technologies, the company that owns The Security Buddy.

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