Machine Learning Algorithms

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Chapter Summaries

luonut Shellena Agustin

Mid over Math 280

luonut yasmin ahmed

Veer's Math IA

luonut Veer Sandhu

🙌🏼 MTE 280 🙌🏼

luonut Connor Berggren

Machine Learning Algorithms Grouped By Similarity

Others

Feature selection

Performance measures

Algorithm accuracy evaluation

SVR

SVM

Ensemble

GBRT

Blending

AdaBoost

Bagging

Boosting

GBM

Random Forest

Dimensionality Reduction

LDA

RDA

QDA

MDA

Partial Least Squares Discriminant Analysis

Projection Pursuit

MDS

Sammon Mapping

PLSR

PCR

PCA

Deep Learning

Stacked Auto-Encoders

CNN

DBN

DBM

Artificial Neural Networks

RBFN

Hopfield Network

Back-Propagation

Perceptron

Rule System

RIPPER

ZeroR

OneR

Cubist

Association rule learning

Eclat

Apriori

Clustering

Hierarchical Clustering

Expectation Maximization

k-Medians

k-Means

Bayesian

BN

Multinomial Naive Bayes

Gaussian Naive Bayes

BBN

AODE

Navie Bayes

Decision Tree

M5

Conditional Decision Trees

Decision Stump

CHAID

C4.5 & C5.0

ID3

CART

Regularization

LARS

Elastic Net

LASSO

Ridge Regression

Instance Based

LWL

SOM

LVQ

kNN

Regression

Logistic Regression

LOESS

MARS

Stepwise Regression

OLSR

Learner Regression