Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Causes of Similarity-Dissimilarity Effect

Causes of Similarity-Dissimilarity Effect

The similarity-dissimilarity effect, a fundamental concept in social psychology, explains how interpersonal similarities and differences influence attraction and social interactions. This effect is supported by three key psychological perspectives: balance theory, social comparison theory, and consensual validation.Balance Theory and Cognitive ConsistencyBalance theory, developed by Fritz Heider, posits that individuals seek cognitive consistency in their relationships. When two people share...

Review and Preview

Review and Preview

In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...

How Data are Classified: Numerical Data

How Data are Classified: Numerical Data

Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...

Classification of Systems-II

Classification of Systems-II

Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,

Ordinal Level of Measurement

Ordinal Level of Measurement

The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks in the...

How Data are Classified: Categorical Data

How Data are Classified: Categorical Data

A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

APPLICATION OF BIOLOGICAL TISSUE REPAIR STIMULATOR AND SEALANTS IN SURGICAL TREATMENT OF BRONCHOPLEURAL FISTULAS.

Georgian medical news·2023

Same author

Crystal structures and RNA-binding properties of Lsm proteins from archaea Sulfolobus acidocaldarius and Methanococcus vannielii: Similarity and difference of the U-binding mode.

Biochimie·2020

Same author

Use of Fluorescent Nucleotides to Map RNA-Binding Sites on Protein Surface.

Methods in molecular biology (Clifton, N.J.)·2020

Same author

Creating robust, reliable, clinically relevant classifiers from spectroscopic data.

Biophysical reviews·2017

Same author

[Squamous cell carcinoma developing in oral lichen planus].

Der Hautarzt; Zeitschrift fur Dermatologie, Venerologie, und verwandte Gebiete·2013

Same author

Identification and analysis of murine pancreatic islet enhancers.

Diabetologia·2012

Search research articles

Related Experiment Video

Updated: Jun 2, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Class proximity measures--dissimilarity-based classification and display of high-dimensional data.

R L Somorjai¹, B Dolenko, A Nikulin

¹Institute for Biodiagnostics, National Research Council Canada, 435 Ellice Avenue, Winnipeg, MB R3B1Y6, Canada. Ray.Somorjai@nrc-cnrc.gc.ca

Journal of Biomedical Informatics

|May 7, 2011

Summary

This summary is machine-generated.

We developed Class Proximity Planes to visualize and classify high-dimensional data. These projections map instances to a 2D plane, offering new perspectives for analyzing complex datasets.

More Related Videos

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

Quantification of Orofacial Phenotypes in Xenopus

Quantification of Orofacial Phenotypes in Xenopus

Published on: November 6, 2014

Related Experiment Videos

Last Updated: Jun 2, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

Quantification of Orofacial Phenotypes in Xenopus

Quantification of Orofacial Phenotypes in Xenopus

Published on: November 6, 2014

Area of Science:

Machine Learning
Data Visualization
Bioinformatics

Background:

High-dimensional data presents significant challenges for classification and visualization.
Existing methods may not offer a unified approach for simultaneous analysis.
The need for effective tools to interpret complex datasets is critical.

Purpose of the Study:

To introduce and construct Class Proximity Planes for two-class problems.
To extend previous relative distance plane mapping for a more general approach.
To enable simultaneous classification and visualization of many-feature datasets.

Main Methods:

Developed mappings of high-dimensional instances into dissimilarity (distance)-based Class-Proximity Planes.
Utilized two-dimensional coordinate systems where axes represent distances to class proximity measures.
Applied various Class Proximity Projections and their combinations.

Main Results:

Demonstrated the ability to classify and visualize high-dimensional instances effectively.
Compared classification and visualization outcomes across multiple datasets.
Showcased the utility on UCI datasets and a high-dimensional biomedical dataset.

Conclusions:

Class Proximity mappings offer a unified and generalizable framework.
These projections provide diverse perspectives for dataset analysis.
The method proves effective for both general and specialized high-dimensional data.