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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 bmchnonan@unomaha.edu.
MATLAB script for efficiently computing values of permutation entropy from 1D time series in sliding windows
Calculation of the entropy of the batch of images (whole image or patches)
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
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.
The Information & Mutual Information Ratio For Counting Image Local Features and Their Matches
A package for studying how things change together.
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 Experience : Work experience of an individual person Urban : Whether that person belongs to urban area or not
Method to compute the probability of each motif type occurred in horizontal visibility graph
A MLP Neural Network based on Shannon's Entropy of Error as a cost function , for classification.Implemented in Python
Measuring the predictability of renewable generation
Implementation of a Clustering Algorithm based on Renyi's entropy of clusters, in R. A pptx presentation of the algorithm and results included.
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 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
Collection of statistical information about texts using finite context models and generation of automatic text