Skill Assessment Test
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05:00
What is supervised learning?
Learning with labeled data
Learning with unlabeled data
Learning by imitation
Learning from experience
Which algorithm is used for classification tasks?
Linear Regression
K-Means Clustering
Support Vector Machines
Principal Component Analysis
What is overfitting in Machine Learning?
A model that is too simple
A model that performs well on training data but poorly on test data
A model that performs equally on training and test data
A model that is too complex but performs well on test data
What does “feature extraction” involve?
Selecting important features from raw data
Creating new features from existing ones
Scaling features to a common range
Encoding categorical features
Which evaluation metric is used for classification problems?
Accuracy
Mean Squared Error
R-Squared
Precision-Recall
What is the purpose of a “confusion matrix”?
To evaluate classification model performance
To visualize data
To handle missing values
To perform dimensionality reduction
Which technique is used for dimensionality reduction?
Principal Component Analysis
K-Means Clustering
Decision Trees
Neural Networks
What does “ensemble learning” refer to?
Combining multiple models to improve performance
Creating a single complex model
Using a single model for all tasks
Training models with different datasets
Which of the following is a regression algorithm?
Random Forest
Naive Bayes
Support Vector Machines
Linear Regression
What is the “bias-variance tradeoff”?
Balancing model complexity and training error
Balancing training and test data
Balancing feature selection and model performance
Balancing data size and model accuracy
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