Regressions Library Documentation¶
The regressions library is a collection of algorithms for fitting data to different functional models by using linear algebra and machine learning. It can generate the following eight key regression models based on any data set: linear, quadratic, cubic, hyperbolic, exponential, logarithmic, logistic, and sinusoidal. For each model, it outputs the constants of the equation, notable graphical points, and the correlation coefficient, among other useful details.
Guide
- Introduction
- Models
- Analyses
- Equations of Functions
- Derivatives of Functions
- Integrals of Functions
- Roots of Functions
- Critical Values of Derivatives
- Sign Charts of Derivatives
- Intercepts of Graph
- Maxima of Graph
- Minima of Graph
- Extrema of Graph
- Inflection Points of Graph
- Points on Graph
- Accumulation of Function
- Mean Values of Function
- Statistics
- Matrices
- Vectors