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Machine Learning

9 posts, in order

Clustering, classification, association rules and prediction in MATLAB.

Start with part 1

  1. Evolutionary Data Clustering in MATLAB

    Cluster data in MATLAB with GA, PSO, or Differential Evolution, using fixed centers or automatic cluster selection through validity indices.

    YPML101

  2. DBSCAN Clustering in MATLAB

    Implement DBSCAN in MATLAB with core, border, and noise points, two clustering parameters, and an example with irregularly shaped clusters.

    YPML110

  3. Neural Gas and GNG Networks in MATLAB

    Train Neural Gas and Growing Neural Gas networks in MATLAB for prototype learning, clustering, and graph representations of data topology.

    YPML111

  4. Group Method of Data Handling (GMDH) in MATLAB

    Build a polynomial GMDH network in MATLAB with pairwise quadratic neurons, least-squares fitting, validation-based selection, and a regression example.

    YPML113

  5. Linear Discriminant Analysis (LDA) in MATLAB

    Extract supervised linear features in MATLAB with Fisher LDA, within- and between-class scatter, a generalized eigenproblem, and the iris dataset.

    YPML114

  6. Apriori Association Rule Mining in MATLAB

    Mine association rules in MATLAB with Apriori, minimum support and confidence, and reported support, confidence, and lift for each rule.

    YPML115

  7. FP-Growth Association Rule Mining in MATLAB

    Explore an FP-Tree-based association-rule mining example in MATLAB, with frequent itemsets, support, confidence, lift, and a plotted tree.

    YPML116

  8. Time-Series Prediction using GMDH in MATLAB

    Predict a time series with GMDH in MATLAB using lagged inputs, polynomial neurons, validation-based selection, and a global ice-volume example.

    YPML120

  9. Feature Selection using Metaheuristics and EAs

    Select features for neural-network regression in MATLAB with GA, ACO, SA, PSO, or NSGA-II, including fixed-size and multi-objective formulations.

    YPML122