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Machine Learning (2019.9 ~ 2020.1)

HW1

  • Regularized linear model regression
    python3 ./HW1[_class].py <testfile>

HW2

  • Naive Bayes classifier
    python3 ./HW2_1.py
  • Online learning
    python3 ./HW2_2.py <testfile>

HW3

  • Sequential Estimator
    python3 ./HW3_1&2.py <mean> <variance>
  • Baysian Linear regression
    python3 ./HW3_3.py

HW4

  • Logistic regression
    python3 ./HW4_1.py [<inputfile>]
  • EM algorithm
    python3 ./HW4_2.py

HW5

  • Gaussian Process
    python3 ./HW5_1.py
  • SVM on MNIST dataset
    python3 ./HW5_2.py {1|2|3}
  • Report

HW6

  • Kernel K-Means
    ./KernelKMeans.sh <k-cluster> <imagename> {kmeans++|mod|random}
  • Spectral Clustering
    python3 ./SpectralClustring.py <k-cluster> <imagename> {normalized|ratio} {kmeans++|random}
  • Report

HW7

  • Kernel Eigenfaces/Fisherfaces
    python3 ./HW7_1.py {1|2|3}
  • t-SNE
    python3 ./HW7_2.py {tsne|ssne} <perplexity> <interval>
  • Report