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What is the purpose of data preprocessing?

• To clean and prepare data for analysis

• To discover patterns and insights from data

• To classify new data based on labeled data

• To predict continuous outcome variables

What is the main advantage of the K-Nearest Neighbor algorithm?

• Simple to understand and implement

• Handles both numerical and categorical data

• Performs well in multi-class prediction

• Provides information about predictor association

What is the purpose of feature selection in data mining?

• To reduce complexity and improve accuracy

• To detect and remove outlier data points

• To replace missing data with estimated values

• To scale data between 0 and 1

What is the role of Bayes' theorem in the Naive Bayes classifier?

• To calculate conditional probabilities

• To find the most frequent label

• To measure the similarity between data points

• To select the nearest neighbors

Which metric is used to measure the fitness of a regression model?

• Accuracy

• Precision

• Recall

• R-squared

What does the F1 Score measure?

• The number of correct predictions out of all positive classes

• The number of actual positives from all positive predicted classes

• The balance between recall and precision

• The true negative rate

What is the purpose of the ROC Curve?

• To measure the sensitivity and specificity of a model

• To plot the performance of a binary classifier at different threshold values

• To calculate the area under the curve

• To evaluate the accuracy of a classification model

What is the purpose of feature selection in data mining?

• To reduce complexity and improve accuracy

• To detect and remove outlier data points

• To replace missing data with estimated values

• To scale data between 0 and 1

What is the main goal of data mining?

• to store and distribute data

• to run raw data into helpful information

• to classify data for further tasks

• to identify natural group of things based on certain characteristics

Identify the term used to define the task of inferring a model from labeled training data

• unsupervised learning

• supervised learning

• reinforcement learning

• none