The Problem of Overfitting 如果有太多的 features,假设可能与训练数据太匹配了以致于预测未来的数据不准确.如下图: 解决 overfitting 1. 既然是由太多的 features 引起的,那么就排除一些 features 2. Regularization 不变动 features,因为 features 也是带有信息的,但是减少 θj 的数量级 Regularization Cost Function Regularization 各个 θ 的参数越小,…
<Brief History of Machine Learning> 介绍:这是一篇介绍机器学习历史的文章,介绍很全面,从感知机.神经网络.决策树.SVM.Adaboost到随机森林.Deep Learning. <Deep Learning in Neural Networks: An Overview> 介绍:这是瑞士人工智能实验室Jurgen Schmidhuber写的最新版本<神经网络与深度学习综述>本综述的特点是以时间排序,从1940年开始讲起,到60-80…
https://jmetzen.github.io/2015-01-29/ml_advice.html Advice for applying Machine Learning This post is based on a tutorial given in a machine learning course at University of Bremen. It summarizes some recommendations on how to get started with machin…
Common Pitfalls In Machine Learning Projects In a recent presentation, Ben Hamner described the common pitfalls in machine learning projects he and his colleagues have observed during competitions on Kaggle. The talk was titled "Machine Learning Grem…
Practical Machine Learning For The Uninitiated Last fall when I took on ShippingEasy's machine learning problem, I had no practical experience in the field. Getting such a task put on my plate was somewhat terrifying, and even more so as we started t…
Machine Learning Methods: Decision trees and forests This post contains our crib notes on the basics of decision trees and forests. We first discuss the construction of individual trees, and then introduce random and boosted forests. We also discuss…
