# Fuzzy coding, decisions, learning

 This is more for overview of my own than for teaching or exercise. Arithmetic · 'elementary mathematics' and similar concepts Set theory, Category theory Geometry and its relatives · Topology Elementary algebra - Linear algebra - Abstract algebra Calculus and analysis Logic Semi-sorted  : Information theory · Number theory · Decision theory, game theory · Recreational mathematics · Dynamical systems · Unsorted or hard to sort Math on data: Statistics as a field some introduction · areas of statistics types of data · on random variables, distributions Virtues and shortcomings of... on sampling · probability glossary · references, unsorted Footnotes on various analyses Other data analysis, data summarization, learning Data massage Data clustering · Dimensionality reduction · Fuzzy coding, decisions, learning · Optimization theory, control theory Connectionism, neural nets · Evolutionary computing

## Fuzzy coding, decisions, learning

 This article/section is a stub — probably a pile of half-sorted notes, is not well-checked so may have incorrect bits. (Feel free to ignore, fix, or tell me)

### Bayesian learning

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Bayesian learning is a general probablistic approach, mostly specifically used as a probablistic classifier.

Mathematically it is based on any observable attribute you can think of, and the math requires Bayesian inversion (see below).

Many basic implementations also use the Naive Bayes assumption (see below), because it saves a lot of computation time, and seems to work almost as well in most cases.

### Some classifiers

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• Parzen classifier
• Backpropagation classifier

### Markov Models, Hidden Markov Models

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Something like (the simplest possible) Bayesian Belief Networks, but geared to streams of data. Can be seen as a state machine noting the likeliness of each next step based on a number of preceding steps.

The hidden variant only shows its output (and hides the model that produces it), the non-hidden one shows all of its state.

Simple ones are first-order