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So I create clusters like this and StandardScale them

N = 3
D = 3
X,y=make_blobs(n_samples=100,centers=N,n_features=D,random_state=None,cluster_std=2)

df=pd.DataFrame(X)
df['Class']=y
sc = StandardScaler()
del[df['Class']]
df_t = pd.DataFrame(sc.fit_transform(df))

Then I do this

mergings = linkage(row_dist, method='ward')
print(mergings)

And it prints, for example, this [5.40000000e+01 1.06000000e+02 1.44777617e-01 3.00000000e+00] I need to take 5.40000000e+01 1.06000000e+02 and compare it to some other result to get 1.44777617e-01 using ward's method.

I can't figure out how to(or to what even) compare 5.40000000e+01 1.06000000e+02 to get 1.44777617e-01

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