Learn R Programming
⚠️There's a newer version (2.4) of this package.Take me there.

KODAMA (version 1.6)

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 .

Copy Link

Version

Install

install.packages('KODAMA')

Monthly Downloads

747

Version

1.6

License

GPL (>= 2)

Maintainer

Stefano Cacciatore

Last Published

April 18th, 2021

Functions in KODAMA (1.6)

USA

State of the Union Data Set
KODAMA

Knowledge Discovery by Accuracy Maximization
core_cpp

Maximization of Cross-Validateed Accuracy Methods
clinical

Clinical Data of a Cohort of Prostate Cancer Patiens
continuous_table

Continuous Information
categorical_table

Categorical Information
dinisurface

Ulisse Dini Data Set Generator
MetRef

Nuclear Magnetic Resonance Spectra of Urine Samples
grid-internal

Internal Grid Functions
multi_continuous_table

Continuous Information
frequency_matching

Frequency Matching
normalization

Normalization Methods
pls.double.cv

Cross-Validation with PLS-DA.
helicoid

Helicoid Data Set Generator
pca

Principal Components Analysis
lymphoma

Lymphoma Gene Expression Dataset
knn.double.cv

Cross-Validation with k-Nearest Neighbors algorithm.
floyd

Find Shortest Paths Between All Nodes in a Graph
k.test

K-Test of Statistical Association
spirals

Spirals Data Set Generator
loads

Variable Ranking
pls.kodama

Partial Least Squares regression.
knn.kodama

k-Nearest Neighbors Classifier.
mcplot

Evaluation of the Monte Carlo accuracy results
transformy

Conversion Classification Vector to Matrix
txtsummary

Median and Coefficient Interval
swissroll

Swiss Roll Data Set Generator
scaling

Scaling Methods