1. Which of the following is true about unsupervised learning?

Unsupervised algorithm only processes features and does not process tags.

Dimensionality reduction algorithm is not unsupervised learning.

K-means algorithm and SVM algorithm belong to unsupervised learning.

None of the above

2. What are the commonly used kernel functions in Support Vector Machine? (choose all that apply)

Gaussian kernel function

Sigmiod kernel function

Polynomial kernel function

Linear kernel

3.What does not belong to supervised learning?

Principal component analysis

Support vector machine

Logistic regression

Decision tree

4.Training error will reduce the accuracy of the model and produce under-fitting. How to improve the model fit? (choose all that apply)

Add features

Feature Engineering

Increase the amount of data

Reduce regularization parameters

5.The following about KNN Algorithm k The value description is correct? (choose all that apply)

K The larger the value, the smoother the segmentation surface of the classification

K The larger the value, the easier the model is to overfit.

can k Value is set to 0

K Value is a hyperparameter