CR.Sparse
v0.1.6
Contents:
Introduction
Tutorials
Getting Started
Fourier and Wavelet Representations
CR.Sparse API Documentation
Digital Signal Processing
Wavelets
Sparsifying Dictionaries and Sensing Matrices
Linear Operators
Greedy Sparse Recovery/Approximation Algorithms
Convex Optimization based Sparse Recovery/Approximation Algorithms
Sample Data Generation Utilities
Utilities in cr.sparse module
Array data type utilities
Metrics for measuring signal and error levels
cr.sparse.metrics.mean_squared
cr.sparse.metrics.mean_squared_error
cr.sparse.metrics.root_mean_squared
cr.sparse.metrics.root_mse
cr.sparse.metrics.normalized_root_mse
cr.sparse.metrics.peak_signal_noise_ratio
Some checks and utilities for matrices (2D arrays)
Row wise and column wise norms for signal/representation matrices
Sparse representations
Linear Algebra Subroutines
Numerical Optimization Routines
Evaluation Framework
Examples Gallery
Benchmarks
Acronyms
References
CR.Sparse
»
CR.Sparse API Documentation
»
Utilities in cr.sparse module
»
cr.sparse.metrics.root_mse
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cr.sparse.metrics.root_mse
¶
cr.sparse.metrics.
root_mse
(
array1
,
array2
)
[source]
¶
Returns the root mean square error between two arrays
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