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Download and install our software tools for your application.
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Applications require 32-bit Windows. Some applications require Microsoft Excel for the User Interface. Libraries require Microsoft Visual C++. Contact us about versions for other operating systems (such as Linux or Solaris), about site licenses, or about academic discounts.
Artificial Intelligence and Expert Systems
NNetSheet Excel-based neural network
toolkit
Induce-It Excel-based case-based
reasoning system
Statistics
RunPCA Principal components analysis
KernelNet Kernel regression
Utilities
Tools and Libraries: Purchase Student Versions
(c) 2006 Inductive Solutions, Inc. All rights
reserved.
GenSheet Excel-based genetic algorithm
toolkit for optimization
Genetic algorithms for
optimizing binary, integer, real, and permutation valued functions that you can create
on any Excel spreadsheet; includes commands for
constrained nonlinear optimization, classifiers, scheduling, and minimum
variance portfolio computation. Genetic algorithms are inspired by Darwinian evolution:
over time, an initial population of answers improve and converge to
a population of optimal answers.
Neural network algorithms for supervised learning
(perceptron, delta rule, generalized delta rule with back propagation)
and unsupervised learning (Hamming, Fuzzy Hamming, and Euclidean clustering).
Creates case-based reasoning
expert systems from Microsoft Excel spreadsheet databases. Induce-It
searches a case database based on
similarity metrics. Case-based are
adapted from the closest matching cases, ranked by case score, and displayed
to users in a sorted list.
RunRandom Quasi-random number and vector
generation
A Random number generation tool and C/C++ library based on
Quasi-Random (Low Discrepancy Sequences) and Pseudo-Random vector
generation algorithms. Quasi-random numbers have better convergence properties
in many simulation applications. RunRandom includes high dimensional (up
to 5000 dimensions) generators for several
low discerepancy sequences.
Principal component analysis useful for
reducing the complexity of high dimensional data: a high dimensional data set can
be approximated with fewer dimensions. PCA is used in datamining
and for pre-processing input data for neural networks and regression. RunPCA includes
a PCA application and C/C++ library.
Non-parametric
multivariate kernel regression
(also known as General Regression Neural Networks) is used for pattern
recognition and forecasting that is based on discovering the underlying probability density of
the observed data. KernelNet includes a kernel regression application and
C/C++ library. KernelNet uses a variation of Sliced
Inverse Regression (SIR) for dimension reduction
to improve efficiency.
Excel-to-XML Translator
A utility that translates Excel
spreadsheet databases to XML.