Python Bytes - Machine Learning Birch Part 4 Subcluster Prediction Value Counts Code in Description
#Coded by Andrew C
import pandas as pd
from sklearn import datasets
wine_dataset = datasets.load_wine()
wine = pd.DataFrame(wine_dataset.data, columns=wine_dataset.feature_names)
from sklearn.preprocessing import StandardScaler
import numpy as numpy
from sklearn.cluster import Birch
X = wine[['alcohol', 'total_phenols']]
scale = StandardScaler()
scale.fit(X)
X_scaled = scale.transform(X)
BRC = Birch(branching_factor=50, n_clusters=None, threshold=.5)
BRC.fit(X_scaled)
y_pred = BRC.predict(X_scaled)
unique_values, counter=numpy.unique(y_pred,return_counts=True)
print("Values in each cluster:")
print(dict(zip(unique_values,counter)))
#coding #datascience #python
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