Complex objects are described by a large number of parameters, and it is often desirable to reduce the dimensionality of descriptions, say for the purposes of easier parameterization, optimization or visualization. pSeven Core has several tools handling most aspects of dimensionality reduction.
If a collection of objects is represented as a set of multi-dimensional points, the tool approximates this set with a smooth hyper-surface and produces compression and decompression procedures which allow the user to:
The tool contains several different nonlinear unsupervised dimension reduction techniques, so that the most appropriate technique can be chosen depending on the amount, dimensionality and noisiness of data.
The reduced dimensionality can be selected manually or it can be found automaticallybased on the desired compression/reconstruction error.
This tool finds linear combinations of the original parameters (features) having the greatest influence on the response function.