Which method is most commonly used in data mining to predict future trends based on historical data?
- Association Rule Mining
- Dimensionality Reduction
- Support Vector Machines
- Time Series Analysis
Time Series Analysis is commonly used in data mining to predict future trends based on historical data. It involves analyzing and modeling data points over time to identify patterns and make predictions. Dimensionality Reduction, Association Rule Mining, and Support Vector Machines serve different purposes in data mining.
Loading...
Related Quiz
- What is the first step in the problem-solving process?
- For a detailed examination of what changed between two commits, the Git command is 'git _______.'
- Which dplyr function is used to summarize data, like calculating the mean of a column?
- In a project facing unexpected challenges, what critical thinking approach should a project manager take to re-evaluate the project plan?
- What is the primary difference between SOAP and REST APIs in terms of their communication protocols?