Use case: Predicting house prices based on area, age, and features.This regression model fits a line to the data using a single dependent variable and one or more independent variables. The three common machine learning models are: Regression models are used to predict continuous values. Use case: detecting objects and animals in images.Capable of learning complex patterns from large datasets.Flexible and powerful models inspired by the human brain.Use case: predict which species a plant belongs to based on its measurements.Helps to improve the model’s generalization performance.Helps to overcome the overfitting problem in individual trees.An ensemble approach combining multiple decision trees.Use case: classify text documents into categories.Can work with both linear and non-linear data.Can be extended to multi-class problems.Binary classifiers that find the hyperplane that best separates data points from different classes.Use case: diagnosing a disease based on symptoms and test results.
Easy interpretation and data visualization.A tree structure splits the data into subsets, with each split being based on the most informative feature.Classification ModelsĬlassification models are used to predict class labels. There are two primary types of supervised learning:Ģ. It seeks to generalize patterns discovered in previously seen data so that it can predict unseen data by mapping inputs to outputs. Supervised learning involves training a model on labeled data, which means the input-output pairs are known. Challenges and Considerations of Machine Learning.Popular Reinforcement Learning Algorithms.
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