Algorithm

• Linear Regression
  • OLS - Ordinary Least Square
  • Gradient Descent
  • library implementation
• PCA - Principal components analysis
• Classifier
  • Nearest Neighbors
  • SVM
  • Gaussian Process
  • Decision Tree
  • Random Forest
  • AdaBoost
  • Naive Bayes
  • QDA
• Dimension Reduction
  • PCA
  • eigenvector
  • t-SNE
• Decision Tree
  • Information Theory
  • Pruning
  • Methods
• Random Forest
  • Randomize methods
• Gradient Boosting Decision Tree
  • XGBoost
  • Light GBM
  • CatBoost

Measurement

• Image Measurement
  • MSE
  • PSNR
  • SSIM
  • MOS
  • LPIPS

Logistic Regression

Support Vector Machine, SVM

Support Vector Machine

K-Nearest Neighbors,KNN

supervised learning For classification:
Given a test instance i, find the k closest neighbors and their labels
Predict i’s label as the majority of the labels of the k nearest neighbors

For regression:
Given a test instance i, find the k closest neighbors and their value
Predict i’s value as the mean of the value of the k nearest neighbors

Could be used directly without training. “Training” process is building a index for searching neighbors faster. small k-> overfitting
large k-> underfitting

K-Means

clustering

Naive Bayes