CAIM Discretization
Algorithm
The CAIM (class-attribute interdependence maximization)
algorithm discretizes a continuous feature into a number of intervals. This is done by using class information, without requiring
the user to provide this number. For more information see ...(Read more)
CLIP4 Algorithm: Hybrid
inductive machine learning algorithm that generates inequality rules
The unique feature of the algorithm is
generation of rules that involve inequalities. The algorithm works with the
data that have large number of examples and attributes, can cope with noisy
data, and can use numerical, nominal, continuous, and missing-value attributes.
The algorithm’s flexibility and efficiency are shown on several well-known
benchmarking data sets, and the results are compared with other machine
learning algorithms...(Read
more)
DataSqueezer: Rule Learner Algorithm
DataSqueezer is an efficient rule builder
that generates a set of production rules from labeled input data.It can handle missing data and has log-linear
asymptotic complexity with the number of training examples.(
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more)
mi-DS: Multiple-Instance Learning
Algorithm
mi-DS is a
multiple-Instance learning supervised algorithm based on the DataSqueezer algorithm.(
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Visualization of Highly-Dimensional Data
Sammon projection, SOM, Molecular Dynamics
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urCAIM
Discretization Algorithm