Skip to content

Regression

Jump to bottom Edit New page
Oscar Serra edited this page Feb 23, 2015 · 4 revisions

By regression we understand the desire of predicting/anticipating the outcome of a situation/episode/example we have observed a number of times in the past (in fact, <math>M_{train}+M_{test}</math> times, see cross-validation). It can be used in a number of cases including time series prediction. The Machine Learning algorithms presented in this section are somewhat simple to implement and generally not very performant. Software packages like Microsoft Excel are prepared to do Linear Regression.

Algorithms

Add a custom footer
  1. Machine Learning
    1. Regression
    2. Classification
    3. Ensembling
    4. Evaluation Metrics
    5. Dimensionality Reduction
    6. Neural Networks
    7. Convex Solvers
    8. Unsupervised Learning
  2. Deep Learning
    1. Basic Neural Networks
    2. Multilayer Neural Networks
Clone this wiki locally