PCA. Theory, uses and implementation.

Work by: Momchil Georgiev

Personal email: [email protected]

Every work cited in this project has been acquired legally through public domains such as university websites, online publications and personal/company blogs.

Description

Contents:

1. Project Motive

2. PCA and the theory behind it:

2.1 Standardize the data

2.1.1 Calculating the mean

2.1.2 Calculating the variance

2.1.3 Calculating standard deviation

2.2 Eigenvectors and eigenvalues of the covariance matrix

3. Some other examples of PCA:

3.1 Breast cancer dataset

3.2 Eigenfaces

4. Conclusion

5. References

6. Bibliography