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Database and Machine Learning Quiz

Authored by Garvit Dohere

Science

12th Grade

Used 2+ times

Database and Machine Learning Quiz
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20 questions

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1.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

What is the purpose of regularization in machine learning?

To reduce bias in the model.

To reduce variance in the model.

To prevent overfitting by penalizing large model coefficients.

To speed up the training process.

2.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

What is the primary objective of supervised learning in machine learning?

To uncover hidden patterns in unlabeled data.

To classify data into predefined categories based on labeled examples.

To learn from interactions with an environment and optimize rewards.

To discover meaningful clusters within a dataset.

3.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

What does the term "overfitting" refer to in machine learning?

When a model fails to capture underlying patterns in the data.

When a model performs well on training data but poorly on unseen data.

When a model is too simple to represent the complexity of the data.

When a model performs equally well on both training and test data.

4.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

Which data structure is typically used to implement a priority queue?

Stack

Queue

Linked List

Heap

5.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

Which algorithm is commonly used to find the shortest path in a weighted graph?

Depth-First Search (DFS)

Breadth-First Search (BFS)

Dijkstra's Algorithm

Prim's Algorithm

6.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

What is the primary goal of unsupervised learning in machine learning?

To classify data into predefined categories based on labeled examples.

To learn from interactions with an environment and optimize rewards.

To discover hidden patterns or structures within a dataset without labeled examples.

To predict a continuous value based on input features.

7.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

Which of the following is NOT a type of database integrity constraint?

Entity Integrity

Referential Integrity

Domain Integrity

Structural Integrity

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