import codecademylib3_seaborn
from sklearn.datasets import load_breast_cancer
breast_cancer_data = load_breast_cancer()

from sklearn.model_selection import train_test_split

training_data, validation_data, training_labels, validation_label = train_test_split(breast_cancer_data.data, breast_cancer_data.target, test_size = 0.2, random_state = 100)

from sklearn.neighbors import KNeighborsClassifier


x = []
y = []
for k in range(1,101):
  classifier = KNeighborsClassifier(n_neighbors = k)
  classifier.fit(training_data, training_labels)
  x.append(k)
  y.append(classifier.score(validation_data, validation_label))

import matplotlib.pyplot as plt

plt.plot(x, y)

plt.xlabel("k")
plt.ylabel("Validation Accuracy")
plt.title("Breast Cancer Classifier Accuracy")

plt.show()