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Full-Text Articles in Other Mathematics
On The Application Of Principal Component Analysis To Classification Problems, Jianwei Zheng, Cyril Rakovski
On The Application Of Principal Component Analysis To Classification Problems, Jianwei Zheng, Cyril Rakovski
Mathematics, Physics, and Computer Science Faculty Articles and Research
Principal Component Analysis (PCA) is a commonly used technique that uses the correlation structure of the original variables to reduce the dimensionality of the data. This reduction is achieved by considering only the first few principal components for a subsequent analysis. The usual inclusion criterion is defined by the proportion of the total variance of the principal components exceeding a predetermined threshold. We show that in certain classification problems, even extremely high inclusion threshold can negatively impact the classification accuracy. The omission of small variance principal components can severely diminish the performance of the models. We noticed this phenomenon in …
Application Of Randomness In Finance, Jose Sanchez, Daanial Ahmad, Satyanand Singh
Application Of Randomness In Finance, Jose Sanchez, Daanial Ahmad, Satyanand Singh
Publications and Research
Brownian Motion which is also considered to be a Wiener process and can be thought of as a random walk. In our project we had briefly discussed the fluctuations of financial indices and related it to Brownian Motion and the modeling of Stock prices.