Supervised learning, semi-supervised learning and unsupervised learning

Supervised learning

     Data Features : feature tag +

      Model:      K neighbors (KNN), decision trees (DT), Naive Bayes (NB), logistic regression (LR), linear regression (LR), support vector machine (SVM), an integrated algorithm (bagging algorithm and Boosting algorithm) ,Neural Networks

Semi-supervised learning (specific reference to Zhou Zhihua watermelon book)

     Data Features : wherein wherein a label portion +

     Model : semi-supervised classification, semi-supervised return, semi-supervised clustering, semi-supervised dimensionality reduction

Unsupervised Learning

     Data Features : Only features

     Model : dimensionality reduction algorithm (PCA, Kernel-PCA, LLE manifold learning, etc.), clustering (kmeans, DBscan, Gaussian mixture clustering, agens, etc.), self-encoded, against generate a network (GAN)