Rerun of machine learning

wonderfuldistinctIA et Robotique

16 oct. 2013 (il y a 5 années et 2 mois)

98 vue(s)

Rerun of machine learning

Clustering and pattern recognition

ikipedia entry on machine learning

7.1 Decision tree learning

7.2 Association rule learning

7.3 Artificial neural networks

7.4 Genetic programming

7.5 Inductive logic programming

7.6 Support vector machines

7.7 Clustering

7.8 Bayesian networks

7.9 Reinforcement learning

7.10 Representation learning

7.11 Sparse Dictionary Learning

And many are still missing (ant colonies; game theory; Laplace
approximations; maximum entropy

Supervised versus unsupervised

Some methods really learn by themselves, but
others are based on a training and testing set.

Clustering or rules

Most times machine learning is used to cluster
groups of data.

It is also possible to find trends or rules with no
clusters involved.

Force fields

There is a whole class of machine learning
algorithms that use force fields (especially if
clustering is involved).

These will be discussed separately.


It normally is not easy to determine which
method to use given the problem at hand. Some
rules of thumb:

1) If you feel that a force field could do the job,
but you also feel that there is a non
relation between data and response, then use
an artificial neural network.

2) When dealing with optimisation in a high
dimensional space, look into genetic algorithms.

3) When clustering things without clearly
detectable clusters, look into

4) When you have much more data than is
needed, look into random forest methods.

5) When it seems clear how to deal with the
data, but there are too many choices, look into
decision tree methods.

6) When dealing with sequence