Why Jupyter is unable to allocate 1.00 GiB for an array

On Jupyter Notebook I am trying to know the best number of clusters of KMeans function by getting the silhouette score.

df = pd.read_csv('single_family_home_values.csv')

X = df.drop('estimated_value', axis=1)

X = X[['bedrooms','bathrooms','rooms','squareFootage','lotSize','yearBuilt','priorSaleAmount']]

X.fillna(0, inplace=True)

for i in range(3, 10):
    kmean = KMeans(n_clusters=i).fit(X)
    labels = kmean.labels_
    print(silhouette_score(X,labels))

But it outputs a Memory error

MemoryError                               Traceback (most recent call last)
<ipython-input-36-ca9617d8baf5> in <module>
      2     kmean = KMeans(n_clusters=i).fit(X)
      3     labels = kmean.labels_
----> 4     print(silhouette_score(X,labels))

MemoryError: Unable to allocate 1.00 GiB for an array with shape (8947, 15000) and data type float64

I have tried closing all tabs and windows and I gave Jupyter Notebook administrator privileges. It was suggested in another question that this is due to the system's overcommit handling mode, but I don't know how to change the overcommit handling mode on Windows and I have read a lot of times that changing it is not recommended. I tried to increase the max buffer size to 4 GB and I have increased the pagefile initial size to 24000 MB and maximum size to 72000 MB, but these solutions did not work.

I have tried running the file in VSC instead and the same error occured.

I am using 64-bit Windows 10 and 16.0 GB of RAM

Here is the csv file: single_family_home_values.csv

Here is the Jupyter config file: jupyter_notebook_config.py