Benutzer:MovGP0/Machine Learning

aus Wikipedia, der freien Enzyklopädie
Zur Navigation springen Zur Suche springen
   MovGP0        Über mich        Hilfen        Artikel        Weblinks        Literatur        Zitate        Notizen        Programmierung        MSCert        Physik      


Machine Learing

[Bearbeiten | Quelltext bearbeiten]

Machine Learning Algorithms[1]

[Bearbeiten | Quelltext bearbeiten]
Regression
Regularization
Instance-based

cake-based, memory-based

Dimensionality reduction
Deep Learnig
  • Deep Boltzmann Machine (DBM)
  • Deep Belief Networks (DBN)
  • Convolutional Neural Network (CNN)
  • Stacked Auto-Encoders
Associated Rule
  • Apriori
  • Eclat
  • FP-Growth
Ensemble
  • Gogit 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)
  • Bayesian Network (BN)
  • Hidden Marhov Models
  • Conditional random fields (CRFs)
Decision tree
  • Classification and Regression Tree (CART)
  • Iterative Dichotomiser 3 (ID3)
  • C4.5 and C4.5
  • Chi-squared Automatic Interaction Detection (CHAID)
  • Decision Stump
  • M5
  • Random Forests
  • Conditional Decision Trees
Clustering
  • Single-linkage clustering
  • k-Means
  • k-Medians
  • Expectation Maximisation (EM)
  • Hierarchical Clustering
  • Fuzzy Clustering
  • DBSCAN
  • OPTICS algorithm
  • Non Negative Matrix Factorization
  • Latent Dirichlet allocation (LDA)
Neural Networks
  • Self-Organizing Map
  • Perceptron
  • Hopfield Network
  • Radial Basis Function Network
  • Backpropagation
  • Autoencoders
  • Boltzmann Machines
  • Restricted Boltzmann Machines
  • Spiking Neural Networks
  • Learing Vector Quantization (LVQ)
Others
  1. Anubhav Srivastava: Which are the best known machine learning algorithms? In: Think Big Data. 9. April 2016, abgerufen am 2. Juli 2016 (englisch).