K-Nearest Neighbor(KNN) Algorithm Quiz

What type of algorithm is K-Nearest Neighbor(KNN)?

• Reinforcement Learning

• Semi-Supervised Learning

• Supervised Learning

• Unsupervised Learning

What does K-NN algorithm assume about the new data and available data?

• No assumption

• Dissimilarity

• No similarity

• Similarity

What is the K-NN algorithm used for mostly?

• Dimensionality Reduction

• Clustering

• Regression

• Classification

What type of algorithm is K-NN?

• Parametric

• Non-parametric

• Supervised

• Unsupervised

What is the main disadvantage of the K-NN algorithm?

• High computation cost

• No need to determine the value of K

• Noisy training data

• Low computation cost

How does K-NN algorithm work?

• Calculating the Euclidean distance

• Calculating the Hamming distance

• Calculating the Minkowski distance

• Calculating the Manhattan distance

What is the most preferred value for K in the K-NN algorithm?

• 3

• 7

• 1

• 5

What is the purpose of the Data Pre-processing step in the K-NN algorithm?

• Feature Scaling

• Model Fitting

• Data Augmentation

• Data Visualization

What does the KNeighborsClassifier class of Sklearn Neighbors library define?

• Type of metric

• Distance between the points

• Type of algorithm

• Number of neighbors

What does the parameter 'p=2' in the KNeighborsClassifier class represent?

• Hamming distance

• Manhattan distance

• Euclidean distance

• Minkowski distance