Quiz | Croma Campus

Which technique is used to generate synthetic samples from an existing dataset to balance class distribution?

SMOTE
ADASYN
NearMiss
All of the above

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Which type of learning algorithm attempts to mimic the way the human brain works?

Supervised Learning
Unsupervised Learning
Reinforcement Learning
Neural Network Learning

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Which of the following is NOT a subfield of AI?

Natural Language Processing (NLP)
Robotics
Calculus
Machine Learning

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Which technique is used to evaluate the importance of each feature in a machine learning model?

Feature Selection
Feature Extraction
Feature Engineering
All of the above

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What is the main purpose of a confusion matrix?

To visualize the performance of a classification model
To calculate the accuracy of a regression model
To estimate the confidence interval of a prediction
To measure the variance of a model

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Which technique is used to make decisions in uncertain and complex environments?

Fuzzy Logic
Genetic Algorithms
Reinforcement Learning
Bayesian Networks

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Which type of validation technique involves dividing the dataset into k equal-sized subsets?

Holdout Validation
Cross-Validation
Leave-One-Out Validation
Random Sampling

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What is the purpose of dimensionality reduction in machine learning?

To increase the complexity of the model
To reduce overfitting
To decrease computational efficiency
To increase computational efficiency

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Which technique is used to handle missing data in a dataset?

Mean Imputation
Median Imputation
Mode Imputation
All of the above

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What is the term used to describe the difference between predicted values and actual values in regression analysis?

Error
Loss
Residual
Deviance

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What is the process of extracting meaningful information from text called?

Text Mining
Text Understanding
Information Retrieval
Text Analysis

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What is the main drawback of oversampling techniques?

Increased risk of overfitting
Decreased computational efficiency
Loss of information
Sensitivity to outliers

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What is the primary goal of Artificial Intelligence (AI)?

To replace human intelligence
To replicate human intelligence in machines
To automate all human tasks
To develop intelligent systems that can perform tasks that typically require human intelligence

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What is the main advantage of ensemble learning algorithms?

Reduced computational complexity
Improved predictive performance
Increased interpretability
Lower risk of overfitting

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Which technique is used to minimize errors in a neural network by adjusting the weights of connections between neurons?

Backpropagation
Gradient Descent
Forward Propagation
Stochastic Gradient Descent

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What is the main objective of supervised learning?

To learn from unlabeled data
To learn from labeled data
To learn from reinforcement
To learn from human experts

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What is the main drawback of rule-based expert systems?

Limited scalability
Difficulty in knowledge acquisition
Inability to handle uncertainty
High computational complexity

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Which technique is used to detect outliers in a dataset?

Z-Score
Interquartile Range (IQR)
Mahalanobis Distance
All of the above

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What is the purpose of the 'exploration' phase in reinforcement learning?

To exploit the current knowledge
To gather new information
To update the policy
To evaluate the reward function

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Which technique is used to recommend items to users based on their past preferences?

Clustering
Collaborative Filtering
Association Rule Learning
Regression

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Which technique is used to measure the similarity between two documents?

Cosine Similarity
Euclidean Distance
Manhattan Distance
Jaccard Similarity

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Which ensemble learning algorithm combines the predictions of multiple base estimators?

Bagging
Boosting
Stacking
All of the above

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Which type of neural network is commonly used for image recognition tasks?

Convolutional Neural Network (CNN)
Recurrent Neural Network (RNN)
Multilayer Perceptron (MLP)
Radial Basis Function Network (RBFN)

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Which technique is used to reduce the dimensionality of data while preserving its variance?

Principal Component Analysis (PCA)
Linear Discriminant Analysis (LDA)
Singular Value Decomposition (SVD)
All of the above

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Which of the following is an unsupervised learning algorithm?

Decision Trees
K-Means
Naive Bayes
Random Forest

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Which algorithm is used to classify data points into multiple classes by building a decision tree?

Decision Trees
Random Forest
K-Nearest Neighbors (KNN)
Support Vector Machines (SVM)

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Which algorithm is commonly used for classification tasks in Machine Learning?

K-Means
Gradient Descent
Support Vector Machines (SVM)
Apriori

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Which algorithm is used to find frequent itemsets in a transactional database?

Apriori
K-Means
DBSCAN
Hierarchical Clustering

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Which technique is used to evaluate the performance of a classification model across different thresholds?

Receiver Operating Characteristic (ROC) Curve
Precision-Recall Curve
Confusion Matrix
All of the above

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What is the main objective of feature scaling in machine learning?

To reduce the number of features
To increase the complexity of the model
To increase the complexity of the model
To ensure that all features have the same scale

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