MACHINE LEARNING
저자: boyapti prasanthi
1. CLUSTERING
1.1. K-Means
1.2. k-Medians
1.3. Expectation maximization
1.4. Hierarchical
1.5. Self-organizing maps
2. DEEP LEARNING
2.1. Multi-layer perceptron
2.2. Recurrent neural networks
2.3. Convolutional neural networks
2.4. Boltzmann machine
2.5. Multi-layer autoencoder
3. CLASSIFICATION
3.1. K-NEAREST NEIGHBOUR
3.2. Support Vector Machine
3.3. Naive Bayes
3.4. Decision tree
4. REGRESSION
4.1. Linear Rgression
4.2. Multivariate linear regression
4.3. Logistic regression
4.4. Cox regression