Machine Learning Algorithms MCQs With Answers

Computer MCQs 360April 19, 2024

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Welcome to the Machine Learning Algorithms MCQs with Answers. In this post, we have shared Machine Learning Algorithms Online Test for different competitive exams. Find practice Machine Learning Algorithms Practice Questions with answers in Computer Tests exams here. Each question offers a chance to enhance your knowledge regarding Machine Learning Algorithms.

Machine Learning Algorithms Online Quiz

By presenting 3 options to choose from, Machine Learning Algorithms Quiz which cover a wide range of topics and levels of difficulty, making them adaptable to various learning objectives and preferences. You will have to read all the given answers of Machine Learning Algorithms Questions and Answers and click over the correct answer.

Test Name: Machine Learning Algorithms MCQ Quiz Practice
Type: Quiz Test
Total Questions: 40
Total Marks: 40
Time: 40 minutes

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Machine Learning Algorithms

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1 / 40

Which algorithm is used for ensemble learning and is based on iteratively combining weak classifiers?

Principal Component Analysis (PCA)

AdaBoost

Linear Regression

2 / 40

Which algorithm is used for handling imbalanced datasets and is based on adjusting class weights during training?

Support Vector Machines

Class Weight Adjustment

Decision Trees

3 / 40

Which algorithm is used for clustering high-dimensional data and is based on iterative optimization of cluster centroids?

K-Means Clustering

Principal Component Analysis (PCA)

Linear Regression

4 / 40

Which algorithm is based on the principle of finding centroids of clusters by minimizing within-cluster variance?

K-Means Clustering

Decision Trees

Logistic Regression

5 / 40

Which algorithm is used for learning hierarchical representations of data and is inspired by the human brain's structure?

Decision Trees

Deep Belief Networks (DBNs)

AdaBoost

6 / 40

Which algorithm is used for sentiment analysis and is based on understanding the context of words in a sentence?

Recurrent Neural Networks (RNNs)

Word2Vec

Long Short-Term Memory (LSTM)

7 / 40

Which algorithm is used for forecasting future values based on time series data and is an extension of ARIMA?

Seasonal ARIMA

Decision Trees

K-Nearest Neighbors

8 / 40

Which algorithm is used for time series forecasting and is based on autoregressive moving average concepts?

ARIMA

Naive Bayes

Decision Trees

9 / 40

Which algorithm is a generative model used for unsupervised learning and is based on graphical models?

Gaussian Mixture Models

Linear Regression

Convolutional Neural Networks (CNNs)

10 / 40

Which algorithm is used for image segmentation and is based on clustering similar pixels together?

K-Means Clustering

Support Vector Machines

Convolutional Neural Networks (CNNs)

11 / 40

Which algorithm is a sequence model commonly used for natural language processing tasks like language modeling and machine translation?

Random Forest

Support Vector Machines

Recurrent Neural Networks (RNNs)

12 / 40

Which algorithm is a probabilistic model commonly used for binary classification tasks?

Random Forest

Logistic Regression

K-Means Clustering

13 / 40

Which algorithm is used for collaborative filtering in recommendation systems and is based on item-item similarities?

Matrix Factorization

Item-based Collaborative Filtering

K-Means Clustering

14 / 40

Which algorithm is used for collaborative filtering in recommendation systems and is based on user-item interactions?

K-Means Clustering

Gradient Boosting

Matrix Factorization

15 / 40

Which algorithm is used for semi-supervised learning and is based on combining labeled and unlabeled data for training?

Label Propagation

Naive Bayes

Support Vector Machines

16 / 40

Which algorithm is used for feature extraction in deep learning and is based on learning hierarchical representations?

Naive Bayes

Gradient Boosting

Autoencoders

17 / 40

Which algorithm is used for predicting probabilities in binary classification and is based on a sigmoid function?

Decision Trees

Support Vector Machines

Logistic Regression

18 / 40

Which algorithm is a deep learning model that excels in image and speech recognition tasks?

Convolutional Neural Networks (CNNs)

K-Means Clustering

Gradient Boosting

19 / 40

Which algorithm is a type of ensemble learning method that combines multiple decision trees to improve performance?

Random Forest

K-Nearest Neighbors

Linear Regression

20 / 40

Which algorithm is used for handling skewed data distributions and is based on logarithmic transformations?

Support Vector Machines

Log Transformation

Decision Trees

21 / 40

Which algorithm is used for classification and regression and is based on the principle of dividing the input space into regions?

Support Vector Machines

Decision Trees

K-Nearest Neighbors

22 / 40

Which algorithm is used for recommendation systems and is based on collaborative filtering?

K-Nearest Neighbors

Logistic Regression

Matrix Factorization

23 / 40

Which algorithm is known for its ability to handle non-linear relationships through the use of kernels?

Naive Bayes

Decision Trees

Support Vector Machines

24 / 40

Which algorithm is a non-parametric method for classification and regression based on similarity to neighboring data points?

Decision Trees

K-Nearest Neighbors

Linear Regression

25 / 40

Which algorithm is used for clustering based on similarity measures such as distance?

Gradient Boosting

Random Forest

K-Means Clustering

26 / 40

Which algorithm is used for reinforcement learning and is based on learning through rewards and punishments?

Q-Learning

Logistic Regression

Principal Component Analysis (PCA)

27 / 40

Which algorithm is used for dimensionality reduction and seeks orthogonal components that capture the maximum variance in data?

Support Vector Machines

Principal Component Analysis (PCA)

Decision Trees

28 / 40

Which algorithm is used for anomaly detection and is based on density estimation?

K-Means Clustering

Support Vector Machines

Gaussian Mixture Models

29 / 40

Which algorithm aims to minimize the variance of predictions by combining multiple weak learners sequentially?

Decision Trees

AdaBoost

Gradient Boosting

30 / 40

Which algorithm is used for sequence-to-sequence learning and is effective for tasks like language translation?

Support Vector Machines

Long Short-Term Memory (LSTM)

AdaBoost

31 / 40

Which algorithm is used for document clustering and topic modeling based on probabilistic inference?

K-Nearest Neighbors

Latent Dirichlet Allocation (LDA)

Support Vector Machines

32 / 40

Which algorithm is used for handling sequential data and is capable of learning long-term dependencies?

Long Short-Term Memory (LSTM)

K-Nearest Neighbors

Decision Trees

33 / 40

Which algorithm is used for image recognition and is based on hierarchical feature learning?

K-Nearest Neighbors

Convolutional Neural Networks (CNNs)

Support Vector Machines

34 / 40

Which algorithm is used for predicting continuous values and is based on finding a line that best fits the data points?

Logistic Regression

Decision Trees

Linear Regression

35 / 40

Which algorithm is used for text classification and is based on the probability of a document belonging to a particular category?

Linear Regression

Gradient Boosting

Naive Bayes

36 / 40

Which algorithm aims to find a linear relationship between input features and output by minimizing the sum of squared errors?

Logistic Regression

Linear Regression

Decision Trees

37 / 40

Which algorithm is used for learning non-linear decision boundaries and is based on kernel functions?

Linear Regression

Support Vector Machines

Logistic Regression

38 / 40

Which algorithm is used for handling missing data and is based on imputing values using nearest neighbors?

K-Nearest Neighbors Imputation

Linear Regression

Random Forest

39 / 40

Which algorithm is used for anomaly detection and is based on fitting a Gaussian distribution to the data?

Random Forest

Gaussian Mixture Models

Gaussian Naive Bayes

40 / 40

Which algorithm is used for nonlinear dimensionality reduction and is based on preserving pairwise distances between data points?

Decision Trees

t-Distributed Stochastic Neighbor Embedding (t-SNE)

Logistic Regression

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Computer MCQs 360April 19, 2024

0 12 1 minute read