Supervised learning, UnSupervised learning Models

지도학습(Supervised learning)

- data x , label y

• k-Neareast Neighbors
• Linear Regression
• Support Vector Machines
• Decision Tree
• Random Forests
• Neural Networks
• Classification, Object Detection, Segmentation, Captioning(DL)

비지도학습(UnSupervised learning)

- only data x

• Clustering (K-Means, Hierachical Cluster Analysis, Expectation Maximization)
• dimensionality reduction(Principal Component Analysis, kernel PCA, LLE, t-SNE)
• Associaiton rule Learning(Apriori, Eclat)
• Feature Learning, Density estimation, Generative Model(DL)