The "heart" of each project are the implemented algorithms. Each algorithm is represented by a subclass of the AbsAlgorithm class with the following methods:
This method takes care of the input of the algorithm: it reads the test case and prepares the data.
The researchers also tested the algorithm on a taxi dispatch problem, where there are a certain number of taxis and the goal is to pick the best locations to cover the maximum number of potential customers.
Of course, the algorithm's potential extends far beyond movie recommendations and taxi dispatch optimizations.
Having a good initialization mechanism is one of the most important aspects of the K-means algorithm. A potential choice for initialization is the insurance that while the K-1 centroids are initialized at random, they are also initialized as far away as possible.
Below is an example of the algorithm's output with different K values, on an image taken from satellite, basically showing how the algorithm can be used for undersegmentation and oversegmentation just by varying its only parameter.
* Are they able to articulate an understanding of the algorithm
and why it works?
PRLSB is a different algorithm
that is based on the same principles as LSB algorithm
Instead, the algorithm
figures out the structure and pattern of the inputs on its own, by mining for rules, detecting patterns and grouping data to help derive meaningful insights.
The SNA[F.sub.3] algorithm
also computes [k.sub.0] to [k.sub.3] by only one comparison-and-shift encoding.