集成学习/02. Boosting 算法.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Boosting 算法的工作机制如下：先从初始训练集训练出一个基学习器，再根据基学习器的表现对训练样本分布进行调整，使得之前错误分类的样本在后续受到更多关注，然后基于调整后的样本分布来训练下一个基学习器，直到基学习器数目达到预设的 T，最终将这 T 个基学习器进行加权结合。\n",
    "\n",
    "Boosting 的代表算法是 AdaBoost。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}