def investigate_knn(iris_data, sel_cols, k_val):
"""
不同的K值对模型的影响
"""
X = iris_data[sel_cols].values
y = iris_data['Label'].values
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=1/3, random_state=10)
knn_model = KNeighborsClassifier(n_neighbors=k_val)
knn_model.fit(X_train, y_train)
accuracy = knn_model.score(X_test, y_test)
print('k={}，accuracy={:.2f}%'.format(k_val, accuracy * 100))
ai_utils.plot_knn_boundary(knn_model, X_test, y_test,
'Sepal Length vs Sepal Width, k={}'.format(k_val),
save_fig='sepal_k={}.png'.format(k_val))
def investigate_pet(iris_data, k_val):
pet_feat_col = ['PetalLengthCm', 'PetalWidthCm']
A = iris_data[pet_feat_col].values
b = iris_data['Label'].values
A_train, A_test, b_train, b_test = train_test_split(A,
b,
test_size=1 / 3,
random_state=10)
knn_model_pet = KNeighborsClassifier()
knn_model_pet.fit(A_train, b_train)
accuracy_pet = knn_model_pet.score(A_test, b_test)
print('K: {} - Petal - Accuracy: {}'.format(k_val, accuracy_pet))
ai_utils.plot_knn_boundary(
knn_model_pet,
A_test,
b_test,
'Petal Length vs Petal Width, k={}'.format(k_val),
save_fig='petal_k={}.png'.format(k_val))
def investigate(iris_data, k_val, sep_feat_col):
X = iris_data[sep_feat_col].values
y = iris_data['Label'].values
X_train, X_test, y_train, y_test = train_test_split(X,
y,
test_size=1 / 3,
random_state=10)
knn_model = KNeighborsClassifier(n_neighbors=k_val)
knn_model.fit(X_train, y_train)
accuracy = knn_model.score(X_test, y_test)
print('K: {} - Sepal - Accuracy: {}'.format(k_val, accuracy))
ai_utils.plot_knn_boundary(
knn_model,
X_test,
y_test,
'Sepal Length vs Sepal Width, k={}'.format(k_val),
save_fig='sepal_k={}.png'.format(k_val))
def investigate_knn(iris_data, sel_cols, k_val):
"""
the different k values influence on model
"""
X = iris_data[sel_cols].values
y = iris_data['label'].values
X_train, X_test, y_train, y_test = train_test_split(X,
y,
test_size=1 / 3,
random_state=10)
knn_model = KNeighborsClassifier(n_neighbors=k_val)
knn_model.fit(X_train, y_train)
acc = knn_model.score(X_test, y_test)
print('k={}, accuracy={:.2f}%'.format(k_val, acc * 100))
plot_knn_boundary(knn_model,
X_test,
y_test,
'PetalLengthCm vs PetalWidthCm, k={}'.format(k_val),
save_fig='Petal_k={}.png'.format(k_val))