Unstop QNA

What is the primary goal of unsupervised learning?

• Minimize prediction errors

• Discover hidden patterns or structures in data

• Classify data into predefined categories

• Optimize model parameters

Which of the following is a classification algorithm?

• Linear regression

• K-means clustering

• Decision tree

• PCA (Principal Component Analysis)

Which evaluation metric is used for imbalanced classification tasks?

• Accuracy

• Precision

• Mean Squared Error (MSE)

• F1-score

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

• Reduce the number of features

• Normalize the distribution of features

• Remove outliers from the dataset

• Encode categorical variables

What does the term "bias" refer to in the context of machine learning models?

• The error due to randomness or variability in the data

• ) The error introduced by overly simplistic assumptions in the model

• The error due to the presence of irrelevant features in the dataset

• The error that occurs when the model fails to capture the underlying patterns in the data

What is the purpose of hyperparameter tuning in machine learning?

• Selecting the most relevant features for the model

• Scaling the input features to a similar range

• Optimizing the model's performance by adjusting parameters

• Splitting the dataset into training and testing sets

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

• The model performs well on the training data but poorly on unseen data

• The model is too simple to capture the underlying patterns in the data

• The model fails to converge during training

• The model's predictions are biased towards a particular class

Which algorithm is used for anomaly detection?

• K-means clustering

• Random Forests

• Isolation Forest

• Linear Regression

What is the main advantage of ensemble learning techniques?

• They are computationally efficient

• They can handle large datasets with high dimensionality

• They improve model performance by combining multiple models

• They are resistant to overfitting

Which algorithm is used for time series forecasting?

• Decision Trees

• Long Short-Term Memory (LSTM)

• K-means clustering

• Linear Discriminant Analysis (LDA)