Cai Cai's Machine Learning Sklearn Class: Understandable from Scratch, from Model Invocation to Practical Implementation

The design of sklearn follows the "Swiss Army Knife" principle, integrating six core modules: Data Preprocessing: Similar to ...
IEEE

Image classification based on improved random forest algorithm

Abstract: An improved random forest node splitting algorithm is proposed in this paper for improving the accuracy of image classification. By recombining the mode of attribute splitting in random ...
GitHub

Forest Cover Type Classification

Predict the forest cover type using cartographic and environmental features from the UCI Covertype dataset. Tree-based models like Decision Tree, Random Forest, and XGBoost are trained and evaluated ...
IEEE

CatBoost and Bayesian Optimization Algorithm-Based Classification of Fraudulently Insured Persons and Random Forest-Based Fraud Prediction Combining Multiple Attention Mechanisms

Abstract: With the development of science and technology, machine learning is gradually applied to the field of insurance to cope with the complex insurance fraud that is difficult to identify by ...
GitHub

Releases: 4GeeksAcademy/machine-learning-python-template-iburgos-random-forest

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