Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Aggregates Classification01:29

Aggregates Classification

346
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
346
Classification of Systems-II01:31

Classification of Systems-II

177
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,
177
Classification of Systems-I01:26

Classification of Systems-I

215
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
215
Tagging and Fusion Proteins01:24

Tagging and Fusion Proteins

6.7K
Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
6.7K
Force Classification01:22

Force Classification

1.3K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
1.3K
Improving Translational Accuracy02:07

Improving Translational Accuracy

11.6K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.6K

You might also read

Related Articles

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

Sort by
Same author

Entropy Gap as a Measure of Epistemic Caution in Credal Sets Generated from Data.

Entropy (Basel, Switzerland)·2026
Same author

A Comparison of Algorithms to Achieve the Maximum Entropy in the Theory of Evidence.

Entropy (Basel, Switzerland)·2026
Same author

A Variation of the Algorithm to Achieve the Maximum Entropy for Belief Functions.

Entropy (Basel, Switzerland)·2023
Same author

Decision Tree Ensemble Method for Analyzing Traffic Accidents of Novice Drivers in Urban Areas.

Entropy (Basel, Switzerland)·2020

Related Experiment Video

Updated: Jul 21, 2025

Flying Insect Detection and Classification with Inexpensive Sensors
05:16

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

25.2K

Upgrading the Fusion of Imprecise Classifiers.

Serafín Moral-García1, María D Benítez1, Joaquín Abellán1

  • 1Department of Computer Science and Artificial Intelligence, University of Granada, 18012 Granada, Spain.

Entropy (Basel, Switzerland)
|July 29, 2023
PubMed
Summary

This study improves imprecise classification by relaxing constraints in combining Imprecise Credal Decision Trees (ICDTs). The new method reduces erroneous predictions compared to the minimum dominance procedure.

Keywords:
Credal Decision Treesbaggingcombination techniqueensemblesimprecise classification

More Related Videos

Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence
09:11

Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence

Published on: January 27, 2023

2.2K
Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing
09:49

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing

Published on: July 5, 2019

9.6K

Related Experiment Videos

Last Updated: Jul 21, 2025

Flying Insect Detection and Classification with Inexpensive Sensors
05:16

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

25.2K
Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence
09:11

Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence

Published on: January 27, 2023

2.2K
Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing
09:49

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing

Published on: July 5, 2019

9.6K

Area of Science:

  • Machine Learning
  • Artificial Intelligence
  • Data Science

Background:

  • Imprecise classification is an emerging ML task where multiple states are identified due to insufficient information.
  • Imprecise Credal Decision Trees (ICDTs) utilize imprecise probabilities and maximum entropy for this task.
  • Combining imprecise classifiers presents challenges, with existing methods risking erroneous predictions.

Purpose of the Study:

  • To enhance the combination of imprecise classifiers.
  • To improve upon existing methods for combining Imprecise Credal Decision Trees (ICDTs).
  • To reduce the risk of erroneous predictions in imprecise classification.

Main Methods:

  • A new procedure for combining imprecise classifiers was developed by relaxing constraints.
  • The new procedure is based on the second-best theory.
  • The proposed method was experimentally compared against the minimum dominance procedure.

Main Results:

  • The new procedure, by relaxing constraints, demonstrated improvement over the minimum dominance method.
  • Experimental studies on a large dataset set showed the effectiveness of the relaxed constraint approach.
  • The enhanced combination method reduced the risk of erroneous predictions.

Conclusions:

  • Relaxing constraints in classifier combination offers a significant improvement for imprecise classification.
  • The second-best theory provides a foundation for developing more robust imprecise classification methods.
  • The developed procedure offers a more reliable approach to combining ICDTs, enhancing predictive accuracy.