Hands on Machine Learning with Scikit -learn Keras and Tensorflow Reading Notes - 算法整理

Jan 4, 2022 · 1 min read · Python MachineLearning Reading Notes  ·
Share on:

  • Supervised learning

    1. k-Nearest Neighbors
    2. Linear Regression
    3. Logistic Regression
    4. SVM
    5. Decision Tree & Random Tree
    6. Neural Network

  • Unsuervised learning

    • Cluster
      1. K-Means
      2. DBSCAN
      3. Hierarchical Cluster Analysis (HCA)
    • Anomaly section and novelty detection
      1. One-class SVM
      2. Isolation Forest
    • Visualization and dimensionality reduction
      1. PCA
      2. Kernel PCA
      3. Locally Linear Embedding (LLE)
      4. t-Distributed Stochastic Neighbor Embedding (t-SNE)
    • Association rule learning
      1. Aoriori
      2. Eclat

  • Semisupervised Learning - Like Google Photo(Identify someone in a photo and system will identify all you in all photos uploaded), most of them will be a combination of Supervised and Unsupervised learning.

    • Deep brief network(DBN) (Based on the restricted Boltzmann machine (RBM))

  • Reinforcement Learning