The only time we are concerned about 2nd Normal Form is when ___________.

• A) Primary key contains redundant values
• B) Primary key is composite
• C) Primary key contains non-unique values
• D) Primary key consists of single attribute

In functional dependency, if one attribute is determinant of all other attributes of the relation then the relation has at least __________.

• A) Random key
• B) Relational key
• C) Super key
• D) Secondary key

A table is in the 2nd Normal Form if there is no___________.

• A) Reflexive dependency
• B) Functional dependency
• C) Transitive dependency
• D) Partial dependency

Consider the following functional dependency: A → B In above functional dependency, attribute B is_______ on A.

• A) Projected
• B) Reflected
• C) Dependent
• D) Terminated

Suppose A → B, then which of the following is valid Functional dependency for augmentation?

• A) AC → BC
• B) A → C
• C) AB → C
• D) AD → B

A relation is in second normal form if and only if ______________ and all the non key attributes are fully functionally dependent on the key.

• A) It is not in first normal form
• B) It has inconsistent data
• C) It is in first normal form
• D) It has multivalued attributes

2nd Normal Form is based on which of the following dependency?

• A) Full functional dependency
• B) Reflexive dependency
• C) Transitive dependency
• D) Partial dependency

In DBSCAN, a point is considered a core point if:

• A) It belongs to two clusters simultaneously.
• B) It is the first point selected.
• C) It has at least the minimum number of neighboring points within a specified radius.
• D) It is far from all other points.

Which two parameters are required by DBSCAN?

• A) Support and Confidence
• B) Eps and MinPts
• C) K and Mean
• D) Learning Rate and Epochs

What does DBSCAN stand for?

• A) Dynamic-Based Statistical Clustering and Analysis Network
• B) Density-Based Systematic Classification Algorithm
• C) Density-Based Spatial Clustering of Applications with Noise
• D) Data-Based Scanning Algorithm

A store discovers the rule: Laptop → Mouse (Confidence = 80%) If 100 customers purchased laptops, how many are expected to purchase a mouse as well?

• A) 20
• B) 80
• C) 50
• D) 100

What is the primary objective of the K-Means algorithm?

• A) Predict future values
• B) Find relationships between variables
• C) Group data into K clusters by minimizing within-cluster variance
• D) Classify data into predefined categories

Which measure indicates how frequently an itemset appears in the transaction database?

• A) Support
• B) Accuracy
• C) Confidence
• D) Lift

Optimization in machine learning refers to:

• A) Increasing storage capacity
• B) Finding parameters that minimize a cost function
• C) Drawing graphs
• D) Removing all data points

A supermarket manager wants to identify products that customers frequently buy together to improve store layout. Which data mining technique should be used?

• A) Clustering
• B) Association Rule Mining
• C) Regression
• D) Classification

A point lies within the Eps distance of a core point but does not have enough neighbors to be a core point itself. What is this point called?

• A) Noise Point
• B) Isolated Point
• C) Cluster Point
• D) Border Point

Suppose a company selects K = 3 for customer segmentation. What does the value 3 represent?

• A) Three clusters to be formed
• B) Three centroids per cluster
• C) Three iterations of the algorithm
• D) Three variables in the dataset

Which formula is commonly used to measure the closeness between a data point and a centroid?

• A) Regression Equation
• B) Mean Formula
• C) Bayes Formula
• D) Euclidean Distance Formula

What happens if the learning rate is too large?

• A) The algorithm may overshoot the minimum
• B) Nothing changes
• C) The algorithm stops immediately
• D) The model becomes perfect instantly

What is the first step in the K-Means algorithm?

• A) Calculate distances
• B) Initialize centroids
• C) Assign data points to clusters
• D) Evaluate cluster quality