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how to perform gridsearchcv on kmeans to find the best clusters with all hyperparamters in gridsearch

Ghanshyam Dhakad answered on October 17, 2023 Popularity 1/10 Helpfulness 1/10

answer how to perform gridsearchcv on kmeans to find the best clusters with all hyperparamters in gridsearch

how to perform gridsearchcv on kmeans to find the best clusters with all hyperparamters in gridsearch

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from sklearn.cluster import KMeans
from sklearn.model_selection import GridSearchCV
from sklearn.datasets import make_blobs

# Generate synthetic dataset
X, _ = make_blobs(n_samples=1000, centers=3, n_features=2, random_state=42)

# Define the parameters for grid search
param_grid = {
    'n_clusters': [2, 3, 4, 5],
    'init': ['k-means++', 'random'],
    'max_iter': [100, 300, 500],
    'tol': [1e-4, 1e-3, 1e-2],
    'algorithm': ['auto', 'full', 'elkan']
}

# Create a KMeans instance
kmeans = KMeans()

# Initialize GridSearchCV
grid_search = GridSearchCV(kmeans, param_grid, cv=5)

# Fit the data to perform the grid search
grid_search.fit(X)

# Print the best parameters and the best score
print("Best parameters found: ", grid_search.best_params_)
print("Best score: ", grid_search.best_score_)

Popularity 1/10 Helpfulness 1/10 Language python

Source: chat.openai.com

Tags: find grid-search k-means python

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Contributed on Oct 17 2023

Ghanshyam Dhakad

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how to perform gridsearchcv on kmeans to find the best clusters with all hyperparamters in gridsearch

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