Machine Learning - Algorithms Cheatsheet

Updated: 2019-01-06

Regression

  • Ordinary Least Squares Regression(OLSR)
  • Linear Regression
  • Logistic Regression
  • Stepwise Regression
  • Multivariate Adaptive Regression Splines(MARS)
  • Locally Estimated Scatterplot Smoothing(LOESS)
  • Jackknife Regression

Regularization

  • Ridge Regression
  • Least Absolute Shrinkage and Selection Operator(LASSO)
  • Elastic Net
  • Least-Angle Regression(LARS)

Instance based, a.k.a. cake-based, memory-based

  • k-Nearest Neighbour(kNN)
  • Learning Vector Quantization(LVQ)
  • Self-Organizing Map(SOM)
  • Locally Weighted Learning(LWL)

Dimensionality Reduction

  • Principle Component Analysis(PCA)
  • Principle Component Regression(PCR)
  • Partial Least Squares Regression(PLSR)
  • Sammon Mapping
  • Multidimensional Scaling(MDS)
  • Projection Pursuit
  • Discriminant Analysis(LDA, MDA, QDA, FDA)

Deep Learning

  • Deep Boltzmann Machine(DBM)
  • Deep Belief Networks(DBN)
  • Convolutional Neural Network(CNN)
  • Stacked Auto-Encoders
  • RNN

Associated Rule

  • Apriori
  • Eclat
  • FP-Growth

Ensemble

  • Logit Boost(Boosting)
  • Bootstrapped Aggregation(Bagging)
  • AdaBoost
  • Stacked Generalization(blending)
  • Gradient Boosting machines(GBM)
  • Gradient Boosted Regression Trees(GBRT)
  • Random Forest

Bayesian

  • Naive Bayes
  • Gaussian Naive Bayes
  • Multinomial Naive Bayes
  • Averaged One-Dependence Estimators(AODE)
  • Bayesian Belief Network(BBN)
  • Bayesion Network(BN)
  • Hidden Markov Models
  • Conditional random fields(CRFs)

Decision Tree

  • Classification and Regression Tree(CART)
  • Iterative Dickotomiser 3(ID3)
  • C4.5 and C5.0
  • Chi-squared Automatic Interaction Detection(CHAID)
  • Decision Stump
  • M5
  • Conditional Decision Trees

Clustering

  • Single-linkage clustering
  • k-Means
  • k-Medians
  • Expectation Maximization(EM)
  • Hierarchical Clustering
  • Fuzzy clustering
  • DBSCAN
  • OPTICS algorithm
  • Non Negative Matrix Factorization
  • Latent Dirichlet allocation(LDA)

Neural Networks

  • Self Organizing Map
  • Perceptron
  • Back-Propagation
  • Hopfield Network
  • Radial Basis Function Network(RBFN)
  • Backpropagation
  • Autoencoders
  • Hopfield networks
  • Boltzmann machines
  • Restricted Boltzmann machines
  • Spiking Neural Networks
  • Leaning Vector Quantization(LVQ)

Others

  • Support Vector Machines(SVM)
  • Evolutionary Algorithms
  • Inductive Logic Programming(ILP)
  • Reinforcement Learning(Q-Learning, Temporal Difference, State-Action-Reward-State-Action(SARSA))
  • ANOVA
  • Information Fuzzy Netowkr(IFN)
  • Page Rank

Based on https://cdn.datafloq.com/cms/2016/04/25/12-algorithms-every-data-scientist-should-know.jpg