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Simple Linear Regression
- A simple linear regression model to predict values based on a linear relationship between variables.
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Support Vector Regression
- A support vector machine algorithm for regression tasks, handling both linear and non-linear data.
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Decision Tree Regression
- A regression model that uses a decision tree to predict outcomes by learning decision rules from features.
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Random Forest Regression
- An ensemble method using multiple decision trees to improve the accuracy and robustness of predictions.
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Logistic Regression
- A statistical model for binary classification tasks, estimating probabilities using a logistic function.
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K Nearest Neighbor
- A non-parametric method used for classification and regression by comparing a point to its k-nearest neighbors.
- K-Means Clustering
- it is an Algorithm used to partition data into K distinct clusters by minimizing the variance within each cluster. It assigns each data point to the nearest cluster centroid and updates centroids iteratively until convergence.