The paper proposes a solution to the problem classification by calculating the sequence of matrices of feature indices that approximate invariants of the data matrix. Here the feature index is the ...

Introduction This project revolves around utilizing and interpreting confusion matrices and related metrics (precision, recall, F1 score) to evaluate multiclass classification predictions in Python.

Abstract: In this paper, we consider the use of convolutive matrix decomposition for matrix data classification. Matrix decomposition has been broadly used as means of dimensionality reduction in a ...

Abstract: Electroencephalogram (EEG) signals are of complex structure and can be naturally represented as matrices. Classification is one of the most important steps for EEG signal processing. Newly ...

Compressed Sensing is a technique used in image acquisition where specific hardware cameras are used to capture images in a compressed manner. The captured images might be as small as 10% of the ...

In a circular issued today, the Securities and Exchange Board of India (Sebi) came out with a risk classification matrix for debt mutual funds which takes both credit and interest rate risk into ...