Question 1

Which algorithm is used for classification in machine learning?

Accepted Answer

Decision Tree

Answer

Regression Analysis

Answer

K-Nearest Neighbor

Answer

Neural Networks

Question 2

What is the purpose of a confusion matrix in machine learning?

Accepted Answer

To evaluate the performance of a classification model

Answer

To visualize the training data

Answer

To preprocess data

Answer

To calculate feature importance

Question 3

Which of the following is NOT a type of supervised learning?

Accepted Answer

Clustering

Answer

Regression

Answer

Association rule learning

Answer

Classification

Question 4

What is the difference between overfitting and underfitting in machine learning?

Accepted Answer

Overfitting occurs when a model is too complex and performs well on training data but poorly on testing data, while underfitting occurs when a model is too simple and performs poorly on both training and testing data.

Answer

Overfitting occurs when a model is not trained enough, while underfitting occurs when a model is trained too much

Answer

Overfitting and underfitting are the same thing

Answer

Overfitting occurs when a model is too simple and performs poorly on both training and testing data, while underfitting occurs when a model is too complex and performs well on training data but poorly on testing data

Question 5

Which of the following is a decision boundary in machine learning?

Accepted Answer

A hyperplane that separates classes in feature space

Answer

The average of all feature values in a data set

Answer

A measurement of model performance

Answer

A type of neural network architecture

Question 6

What is the purpose of cross-validation in machine learning?

Accepted Answer

To assess the performance of a model on an independent data set

Answer

To preprocess data before training a model

Answer

To visualize the data

Answer

To train a model on multiple data sets simultaneously

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