CART

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Cart算法代码:模型预测屏蔽
Python 代码: 在线屏蔽代码:- cartpole_test.py- cartpole_test_bl.py- bicycle_test.py- bicycle_test_bl.py MATLAB 代码: 用于 LQR 验证。依赖项:- SOSTOOLS 3.03- SeDuMi 优化器 基线代码: 依赖项:- Z3 定理证明器
深入探索数据挖掘核心算法:CART详解
数据挖掘十大经典算法之CART 第十章 CART 本章深入探讨数据挖掘十大经典算法之一:CART。内容基于 The Top 10 Algorithms in Data Mining 教材第十章,以23页的篇幅对CART进行详细阐述,涵盖16个小节,并采用英文讲解。
MATLAB Cart Pendulum Template Dynamic Simulation Guide for RDS2020
Cart Pendulum Template for MATLAB - This guide provides an overview of the MATLAB code for simulating the dynamics of a cart-pendulum system using the RDS2020 framework. The primary entry point of the application is main.m, which utilizes various dynamics-related functions through a wrapper. These functions are generated automatically by running derive_equations.m. Important: You must run derive_equations.m before main.m to initialize the required dynamics functions. Workflow: Symbolic Computation: derive_equations.m employs symbolic computation to create the cart-pendulum’s state-space dynamics. It exports this as MATLAB functions (e.g., autogen_drift_vector_field.m and autogen_control_vector_field.m). Controller Design: You can experiment with controller design in main.m. For certain controller types, a middleware layer may be necessary to customize control functionality. Note to Students: This code requires additional setup before it can run. You must complete derive_equations.m where you see TODO lines to finalize certain parts of the code.
CART决策树算法在数据挖掘中的应用研究
分类与回归树CART算法是数据挖掘技术中重要的算法。依据CART算法理论,采用类型变量求解决策树,并引入优化的分裂函数。然后,利用基于类型变量的论域划分创建二叉树,抽取和筛选预测准则,从而为职能部门决策提供科学而可靠的依据。最后,以贵州师范大学教学与管理中的数据,给出算法的应用实例。