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Extreme Optimization Numerical Libraries for .NET
What's New in Version 6.0
Universal improvements
- There now is one setup for both 32 and 64 bit operating systems.
- Libraries can also be installed as NuGet packages, for easier upgrading.
- The documentation has been fully updated to the latest API.
- New and updated QuickStart samples illustrate the new API.
Math Library
- Complex numbers are now generic over the type of the real and imaginary parts.
- Dormand-Prince adaptive RK ODE solver
- Akima splines and cubic Hermite splines.
- Evaluation of orthogonal polynomials.
- Error functions for Quad precision numbers.
- Vector functions for complex single and double precision arguments.
- Faddeeva function, Voigt function, complex error function.
- Savitsky-Golay and Moving Average smoothing in SignalProcessing.
Data Analysis Library
- Support for LINQ queries on data frames, vectors and matrices.
- New groupings for aggregations include: fixed and expanding windows,
partitions, groupings on value and quantiles, 2D pivot tables,
and resampling.
- A large set of aggregators and aggregator functions has been added
with efficient implementations for specific types of groupings
(e.g. moving averages).
- New generic Descriptives class for collecting descriptive
statistics of vectors.
- Indexes on ordered types now support lookup nearest. Likewise,
data frames with such indexes now support join on nearest.
- New Recurrence type lets you specify date/time patterns
for use in, for example, resampling of data frames.
Vector and Matrix Library
- All vector and matrix classes are now generic, including sparse matrices and complex versions.
- New static Vector and Matrix classes remove the need to specify the element type
as a generic type argument.
- New mutability options now let you create read-only vectors, and writable vectors with
copy-on-write semantics.
- Most operations on vectors and matrices are available in three
forms: as a static method that returns a new value, as a static
method that returns the value in a supplied object, and as
an instance method that modifies the object in-place.
- Operator methods are named consistently for static calls,
in-place and out-of-place updates.
- Relational operators are now supported for generic matrices.
- The native libraries have been upgraded to Intel MKL version 11.3
Update 2.
- The native libraries now support Conditional Numerical
Reproducibility.
- The CUDA libraries for 64 bit have been upgraded to CUDA
version 7.5.
- A fully managed implementation of the linear algebra library
for single-precision floating-point numbers was added.
Statistics Library
- Descriptions tailored to working in an interactive environment
for statistical models, hypothesis tests and other objects.
- Statistical models have been integrated with the DataFrame
library.
- The variable types (NumericalVariable, CategoricalVariable,
DateTimeVariable) have been replaced with generic vectors.
- Categorical variables are expanded into indicator variables
when necessary. Several encoding schemes are available.
- Models can be persisted in a form suitable for deployment in
predictive modeling applications.
- Models can be specified using R-style formulas.
- Regression models are now robust against collinearity.
- New distribution classes have been added: truncated distributions,
inverse Weibull.
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