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KODAMA (version 2.4.1)

Knowledge Discovery by Accuracy Maximization

Description

An unsupervised and semi-supervised learning algorithm that performs feature extraction from noisy and high-dimensional data. It facilitates identification of patterns representing underlying groups on all samples in a data set. Based on Cacciatore S, Tenori L, Luchinat C, Bennett PR, MacIntyre DA. (2017) Bioinformatics and Cacciatore S, Luchinat C, Tenori L. (2014) Proc Natl Acad Sci USA .

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Version

Install

install.packages('KODAMA')

Monthly Downloads

108

Version

2.4.1

License

GPL (>= 2)

Maintainer

Stefano Cacciatore

Last Published

November 5th, 2024

Functions in KODAMA (2.4.1)

lymphoma

Lymphoma Gene Expression Dataset
frequency_matching

Frequency Matching
mcplot

Evaluation of the Monte Carlo accuracy results
k.test

K-Test of Statistical Association
helicoid

Helicoid Data Set Generator
loads

Variable Ranking
pls.kodama

Partial Least Squares regression.
pls.double.cv

Cross-Validation with PLS-DA.
pca

Principal Components Analysis
normalization

Normalization Methods
scaling

Scaling Methods
multi_analysis

Continuous Information
spirals

Spirals Data Set Generator
swissroll

Swiss Roll Data Set Generator
txtsummary

Median and Coefficient Interval
transformy

Conversion Classification Vector to Matrix
categorical.test

Categorical Information
KODAMA.matrix

Knowledge Discovery by Accuracy Maximization
core_cpp

Maximization of Cross-Validateed Accuracy Methods
KODAMA.visualization

Visualization of KODAMA output
clinical

Clinical Data of a Cohort of Prostate Cancer Patiens
USA

State of the Union Data Set
continuous.test

Continuous Information
MetRef

Nuclear Magnetic Resonance Spectra of Urine Samples
grid-internal

Internal Grid Functions
correlation.test

Continuous Information
floyd

Find Shortest Paths Between All Nodes in a Graph
knn.double.cv

Cross-Validation with k-Nearest Neighbors algorithm.
knn.kodama

k-Nearest Neighbors Classifier.
dinisurface

Ulisse Dini Data Set Generator