Clustering QUIZ (MCQ QUESTIONS AND ANSWERS)

Divide the data points into groups

Classify the data point into different classes

Predict the output values of input data points

All of the above

Supervised learning

Unsupervised learning

Reinforcement learning

None

K- Means clustering

Hierarchical clustering

Diverse clustering

All of the above

K-means clustering algorithm

K-modes clustering algorithm

K-medians clustering algorithm

None

Data points with outliers

Data points with different densities

Data points with non-convex shapes

All of the above

Labeled data

Unlabeled data

Numerical data

Categorical data

Biological network analysis

Market trend prediction

Topic modeling

All of the above

Time series data

Text data

Multimedia data

None

Supervised learning

Unsupervised learning

Reinforcement learning

All of the above

The number of cluster centroids

The tree representing how close the data points are to each other

A map defining the similar data points into individual groups

All of the above

a distance metric

initial number of clusters

initial guess as to cluster centroids

None

k-means clustering is a vector quantization method

k-means clustering tries to group n observations into k clusters

k-nearest neighbor is same as k-means

None

Hierarchical clustering

Partitional clustering

Density-based clustering

All of the above

cross-validation

the silhouette method

the elbow method

All of the above

After finding no new reassignment of data points

After the algorithm reaches the defined number of iterations

Both A and B

None

K-means

Divisible

Agglomerative

None

K-means

Divisible

Agglomerative

All of the above

Takes each data point as an individual cluster

Goes on making clusters until it reaches to an optimal number of cluster

Follows a top to bottom approach

All of the above

Random forest

Support vector machine

K-means

K-nearest neighbors

A hierarchical structure

A diagram structure

A graph structure

None