Please enable JavaScript.
Coggle requires JavaScript to display documents.
COMP312P - Machine learning (learning methods (supervised learning…
COMP312P - Machine learning
learning methods
supervised learning
linear regression
logistic regression (discrete)
Naive Bayes classifier
discrete Naive Bayes
Gaussian Naive Bayes (probabilistic logistic regression)
Support vector machine
replace inner products w kernel fn
Lagrangian optimisation
SVM classification
SVM regression
multi-class SVM
one-vs-one
one-vs-all
decision trees
entropy, information gain, gini impurity
classification & regression tree (ID3)
random forest
ensemble methods
bagging
boosting (AdaBoost)
unsupervised learning
clustering
k-mean algo
EM steps
self-organising maps
Gaussian mixture model
density estimation
dimensionality reduction
feature selection
feature transformation
linear dimensionality reduction - subspace learning (PCA)
non-linear dimensionality reduction - manifold learning (LLE, Isomap)
vector quantisation
matrix factorisation
model types
parametric
linear regression
neural network
non-parametric
k-nearest neighbour
density kernel functions
univariate
multivariate
Gaussian processes
Pre-processing
feature selection
feature transformation
linear dimensionality reduction - subspace learning (PCA)
non-linear dimensionality reduction - manifold learning (LLE, Isomap)