Question: how would go about making the code below work? Provide code please. from sklearn.preprocessing import StandardScaler standard_scaler = StandardScaler() transformed_features_doc2vec = standard_scaler.fit_transform(features_doc2vec) model_kmeans = KMeans(n_clusters=k,

how would go about making the code below work? Provide code please.

from sklearn.preprocessing import StandardScaler standard_scaler = StandardScaler() transformed_features_doc2vec = standard_scaler.fit_transform(features_doc2vec) model_kmeans = KMeans(n_clusters=k, random_state=20130810) model_kmeans.fit(transformed_features_doc2vec) KMeans(n_clusters=4, random_state=20130810) labels_kmeans = model_kmeans.labels_ silhouette_score(transformed_features_doc2vec, labels_kmeans) for k in [4, 5, 6, 7, 8, 9]: model_kmeans = KMeans(n_clusters=k, random_state=20130810) model_kmeans.fit(transformed_features_doc2vec) sil_score = silhouette_score(transformed_features_doc2vec, model_kmeans.labels_) print(f"k = {k}, silhouette score = {sil_score}")#

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