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kernel PCA

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Hans's notebook

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  - Ax equal b and the Four Subspaces
    Ax equal b and the Four Subspaces
    
    The Geometry of Linear Equations
    
    An Overview of Linear Algebra
    
    Elimination with Matrices
    
    Multiplication and Inverse Matrices
    
    Factorization into A=LU
    
    Transpose, permutations, spaces R^n
    
    Column Space and Nullspace
    
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    Independence, Basis and Dimension
    
    The Four Fundamental Subspaces
    
    Matrix spaces, Rand 1 and Small World Graphs
    
    Graphs, Networks and Incidence Matrices
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    Least Squares Determinants and Eigenvalues
    
    Orthogonal vectors and subspaces
    
    Projections onto Subspaces
    
    Projection Matrices and Least Squares
    
    Orthogonal Matrices and Gram-Schmidt
    
    Properties of Determinants
    
    Determinant Formulas and Cofactors
    
    Cramer's Rule, Inverse Matrix, and Volume
    
    Eigenvalues and Eigenvectors
    
    Diagonalization and Powers of A
    
    Differential Equations and e^At
    
    Markov Matrices and Fourier Series
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    Positive Definite Matrices and Applications
    
    Symmetric Matrices and Positive definiteness
    
    Complex Matrices and Fast Fourier Transform
    
    Positive Definite Matrices and Minima
    
    Similar Matrices and Jordan Form
    
    Singular Value Decomposition(SVD)
    
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    Left and Right Inverse; Pseudoinverse
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kernel PCA

The result of kernel PCA can be seen as follows

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