Data for: QUALITATIVE PATTERN RECOGNITION IN CHEMISTRY: THEORETICAL BACKGROUND AND PRACTICAL GUIDELINES

Name: Data for: QUALITATIVE PATTERN RECOGNITION IN CHEMISTRY: THEORETICAL BACKGROUND AND PRACTICAL GUIDELINES
Creator: Paolo Oliveri
Published: 2020-12-22T21:00:00.911Z
Keywords: Chemometrics

Oliveri, Paolo; Casale, Monica; Malegori, Cristina; Mustorgi, Eleonora

doi:10.17632/pgrdmfyj44.1

Data for: QUALITATIVE PATTERN RECOGNITION IN CHEMISTRY: THEORETICAL BACKGROUND AND PRACTICAL GUIDELINES

Published: 22 December 2020| Version 1 | DOI: 10.17632/pgrdmfyj44.1

Contributors:

Paolo Oliveri, Monica Casale, Cristina Malegori, Eleonora Mustorgi

Description

Simulated dataset for multivariate unsupervised exploratory analysis and supervised classification. 30 samples, equally divided in 3 classes (10 samples per class), and described by 6 descriptor variables.

Data for: QUALITATIVE PATTERN RECOGNITION IN CHEMISTRY: THEORETICAL BACKGROUND AND PRACTICAL GUIDELINES

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