Scott's world.

Week 8

Word count: 56Reading time: 1 min
2019/07/05 Share

Week 8

Clustering

K-Means Algorithm(K均值 (K-means) 算法)

Optimization Objective

Random Initialization

Choosing the Number of Clusters

Motivation

Motivation I : Data Compression

Motivation II:Visualization

Principal Component Analysis(PCA)

Principal Component Analysis(PCA)Problem Formulation

Principal Component Analysisi Algorithm

PCA Applying

Reconstruction from Compressed Representation

Choosing the Number of Principal Components

Advice for Applying PCA

CATALOG
  1. 1. Week 8
    1. 1.1. Clustering
      1. 1.1.1. K-Means Algorithm(K均值 (K-means) 算法)
      2. 1.1.2. Optimization Objective
      3. 1.1.3. Random Initialization
      4. 1.1.4. Choosing the Number of Clusters
    2. 1.2. Motivation
      1. 1.2.1. Motivation I : Data Compression
      2. 1.2.2. Motivation II:Visualization
    3. 1.3. Principal Component Analysis(PCA)
      1. 1.3.1. Principal Component Analysis(PCA)Problem Formulation
      2. 1.3.2. Principal Component Analysisi Algorithm
    4. 1.4. PCA Applying
      1. 1.4.1. Reconstruction from Compressed Representation
      2. 1.4.2. Choosing the Number of Principal Components
      3. 1.4.3. Advice for Applying PCA