C++ Implementation of entropy measures
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Updated
Oct 13, 2017 - C++
C++ Implementation of entropy measures
Collection of statistical information about texts using finite context models and generation of automatic text
MATLAB script for efficiently computing values of permutation entropy from 1D time series in sliding windows
Crypto implementations analysis toolkit
A MLP Neural Network based on Shannon's Entropy of Error as a cost function , for classification.Implemented in Python
Implementation of a Clustering Algorithm based on Renyi's entropy of clusters, in R. A pptx presentation of the algorithm and results included.
Recommendation System support Farmer to prevent The Blast Disease ( Type of Rice Disease )
A program that creates a probabilistic model for a text file counting the number of occurrences of individual letters and also calculates entropy for the probabilistic model
The Information & Mutual Information Ratio For Counting Image Local Features and Their Matches
Calculation of the entropy of the batch of images (whole image or patches)
Use decision trees to prepare a model on fraud data treating those who have taxable_income <= 30000 as "Risky" and others are "Good" Data Description : Undergrad : person is under graduated or not Marital.Status : marital status of a person Taxable.Income : Taxable income is the amount of how much tax an individual owes to the government Work Ex…
This application calculates the entropy of a string. The focus of this implementation is represented by a specialized function called "entropy" which receives a text sequence as a parameter and returns a value that represents the entropy. Entropy is a measure of the uncertainty in a random variable.
Official PyTorch implementation of A Quaternion-Valued Variational Autoencoder (QVAE).
Method to compute the probability of each motif type occurred in horizontal visibility graph
Measuring the predictability of renewable generation
This is a project associated to Computational Geometry as is taught at Madrid's Complutense University by professor Robert Monjo, covering Information Theory matters such as data entropy and compression.
A package for studying how things change together.
This is our standard library for nonlinear analysis. Many of these functions are the same we use in our services. We do have additional methods that are not public but could be made available in a future release. If you are interested in learning more, attending our workshops or webinars or using our data analysis services please contact bmchnon…
Application allows for ifnormation entropy analysis of 2D image data. Analysis outcome can be stored in No-SQL database and then recovered and plotted for better understanding of underlying data
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