Machine Learning Notes, MOOC, W1_Introduction

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1. Definition of Supervised Learning and unsupervised learning

Idea of supervised learning is to teach computer how to do something.

Idea of unsupervised learning is to let the computer learn by itself.

Reinforcement learning: 强化学习

1. Supervised Learning

We give the system a set of dataset, which is a set of "right answers".

It is also called Regress problem: predict a continuous value output.

Classification problem: predict a discrete value.

We could identify a problem whether is a classification one or a regression one by the output value. If it is a discrete value, it should be a classification problem; otherwise, it will be a regression one.

1. Unsupervised Learning

We are given the data without labels. We are not told to do prediction work. Just the dataset, we are asked to find the structure of the dataset.

Clustering problem: kind of similar to the classification problem in supervised learning, the difference is that in unsupervised learning, there is no "correct answer" set that can be used for studying.

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Machine Learning Notes, MOOC, W1_Introduction

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原文地址：http://www.cnblogs.com/csytangresearch/p/3872300.html