# Search for tag: "mathematical sciences"

#### DSPA Chapter 21 Function Optimization

Chapter 21 covers (1) constrained and unconstrained optimization, (2) Lagrange multipliers, (3) linear, quadratic and (general) non-linear programming, and (4) data denoising.

From  Tina Chang 0 likes 28 plays 0

#### DSPA Chapter 18 Big Longitudinal Data Analysis (Timeseries GEE GLMM SEM)

DSPA Chapter 18 Big Longitudinal Data Analysis (Timeseries GEE GLMM SEM)The time-varying (longitudinal) characteristics of large information flows represent a special case of the complexity,…

From  Tina Chang 0 likes 54 plays 0

#### DSPA Chapter 16 (Variable Selection)

DSPA Chapter 16 (Variable Selection) As we mentioned in Chapter 15, variable selection is very important when dealing with bioinformatics, healthcare, and biomedical data where we may have more…

From  Tina Chang 0 likes 34 plays 0

#### DSPA Chapter 4 Linear Algebra and Matrix Computing

DSPA Chapter 4 Linear Algebra and Matrix Computing Linear algebra is a branch of mathematics that studies linear associations using vectors, vector-spaces, linear equations, linear…

From  Tina Chang 0 likes 104 plays 0

#### DSPA Chapter 10: SVM Classification

DSPA Chapter 10 SVM Classification In this chapter, we are going to cover two very powerful machine-learning algorithms. These techniques have complex mathematical formulations, however,…

From  Tina Chang 0 likes 58 plays 0

#### DSPA Chapter 9: Regression Classification

DSPA Chapter 9: Regression Classification In previous chapters (6, 7, and 8), we covered some classification methods that use mathematical formalism to address everyday life prediction problems.…

From  Tina Chang 0 likes 81 plays 0

#### DSPA Chapter 7 Naive Bayes Classification

DSPA Chapter 7 Naive Bayes Classification Please review the introduction to Chapter 6, where we described the types of machine learning methods and presented lazy classification for numerical…

From  Tina Chang 0 likes 85 plays 0