1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | from sklearn.datasets import load_iris from sklearn.model_selection import train_test_split from sklearn.neighbors import KNeighborsClassifier from sklearn import metrics iris = load_iris() num_neigh = 5 knn = KNeighborsClassifier(n_neighbors=num_neigh) knn.fit(iris.data, iris.target) y_pred_all = knn.predict(iris.data) scores = metrics.accuracy_score(iris.target, y_pred_all) print('n_neighbors°¡ {0:d}À϶§ Á¤È®µµ: {1:.3f}'.format(num_neigh, scores)) import matplotlib.pyplot as plt plt.hist2d(iris.target, y_pred_all, bins=(3,3), cmap=plt.cm.jet) plt.show() from sklearn.metrics import confusion_matrix conf_mat = confusion_matrix(iris.target, y_pred_all) print(conf_mat) plt.matshow(conf_mat) plt.show() | cs |