Exploring Lecture 30 20 Nov Cpsc 340 2020w Machine Learning And Data Mining

Exploring Lecture 30 20 Nov Cpsc 340 2020w Machine Learning And Data Mining reveals several interesting facts.

  • Principal Component Analysis,
  • Feature Selection, Genome-Wide Association Studies.
  • More Linear Classifiers, Support Vector
  • Regularization.
  • More clustering, DBSCAN (video, demo), Hierarchical Clustering, Phylogenetic Trees https://www.cs.ubc.ca/~fwood/CS340/

In-Depth Information on Lecture 30 20 Nov Cpsc 340 2020w Machine Learning And Data Mining

Multi-Dimensional Scaling, Nonlinear Dimensionality Reduction, t-SNE demo. Feature Engineering, Gmail Priority Inbox. Kernel Trick. MLE and MAP, Maximum Likelihood Estimation.

Outlier Detection, Empirical Study https://www.cs.ubc.ca/~fwood/CS340/

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