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Decision Trees These trees split data into branches based on feature values, providing clear decision rules. SupportVectorMachines (SVM) SVMs are powerful classifiers that separate data into distinct categories by finding an optimal hyperplane. They are handy for high-dimensional data.
It offers implementations of various machine learning algorithms, including linear and logistic regression , decision trees , random forests , supportvectormachines , clustering algorithms , and more. There is no licensing cost for Scikit-learn, you can create and use different ML models with Scikit-learn for free.
Hybrid machine learning techniques integrate clinical, genetic, lifestyle, and omics data to provide a comprehensive view of patient health ( Image credit ) The choice of an appropriate model is critical in predictive modeling. Ensuring that hybrid models also generalize well to unseen data is a constant concern.
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