Linear regression is a fundamental algorithm used for predictive analysis.Linear regression predicts the probability of a binary outcome (e.g., yes/no, true/false) based on one or more predictor variables.K-Means clustering is an unsupervised learning algorithm used to partition data into distinct clusters based on similarity..Decision trees are versatile algorithms used for both classification and regression tasks..Random Forest is an ensemble learning method that combines multiple decision trees to improve accuracy and reduce overfitting..Read More Stories
Linear regression is a fundamental algorithm used for predictive analysis.Linear regression predicts the probability of a binary outcome (e.g., yes/no, true/false) based on one or more predictor variables.K-Means clustering is an unsupervised learning algorithm used to partition data into distinct clusters based on similarity..Decision trees are versatile algorithms used for both classification and regression tasks..Random Forest is an ensemble learning method that combines multiple decision trees to improve accuracy and reduce overfitting..Read More Stories