What are some examples of robust algorithms?
Robust algorithms are designed to perform well under a variety of conditions. Examples include RANSAC for outlier detection, the Kalman filter for tracking, and the AdaBoost algorithm for improving classification accuracy.
Can you explain how RANSAC works?
Sure! RANSAC, or Random Sample Consensus, iteratively selects random subsets of data to estimate a model, then checks how many data points fit this model within a certain tolerance. It’s great for handling outliers.
What are the applications of the Kalman filter?
The Kalman filter is widely used in robotics for navigation, in finance for predicting stock prices, and in aerospace for tracking the position of aircraft.
How does AdaBoost improve classification accuracy?
AdaBoost combines multiple weak classifiers to create a strong classifier. It focuses on misclassified instances by adjusting their weights, allowing the model to learn from its mistakes.
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