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

Classification of Neurotransmitters01:30

Classification of Neurotransmitters

5.1K
Neurotransmitters play a crucial role in the communication between neurons in the autonomic nervous system. Neurons in the autonomic nervous system can be cholinergic or adrenergic depending on the neurotransmitters synthesized. Cholinergic neurons use acetylcholine as their primary neurotransmitter. This includes all the preganglionic fibers of the sympathetic and pre- and postganglionic fibers of the parasympathetic nervous systems. In addition, neurons of the somatic nervous system also use...
5.1K
Classification of Leukocytes01:30

Classification of Leukocytes

5.2K
Leukocytes are classified into two groups based on the presence or absence of cytoplasmic granules. Granular leukocytes, which contain granules, belong to the myeloid lineage and are divided into three subtypes: neutrophils, eosinophils, and basophils. These cells are roughly spherical and characterized by the granules in their cytoplasm.
Neutrophils are the most abundant type of granular leukocytes, comprising 50-70% of all leukocytes. They feature small, evenly distributed granules and a...
5.2K
Classification of Bones01:18

Classification of Bones

9.7K
The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The...
9.7K
Force Classification01:22

Force Classification

2.3K
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,...
2.3K
Classification of Illness01:17

Classification of Illness

8.6K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
8.6K
Brick Classifications01:16

Brick Classifications

379
Bricks, a fundamental component of construction, are categorized based on their application and structural characteristics into several types. These include facing bricks, building bricks, hollow bricks, paving bricks, and firebricks. Facing bricks, also referred to as face bricks, are primarily used for both structural support and visual appeal, making their appearance a crucial aspect. In contrast, building bricks are typically used in concealed sections of a structure, such as behind the...
379

You might also read

Related Articles

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

Sort by
Same author

Land-Cover Classification Using MaxEnt: Can We Trust in Model Quality Metrics for Estimating Classification Accuracy?

Entropy (Basel, Switzerland)·2020
Same author

Chile unprepared for Ph.D. influx.

Science (New York, N.Y.)·2017
Same author

MaxEnt's parameter configuration and small samples: are we paying attention to recommendations? A systematic review.

PeerJ·2017
Same author

The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project.

Ecology and evolution·2017
Same author

Nitric Oxide Synthase 1 Modulates Basal and β-Adrenergic-Stimulated Contractility by Rapid and Reversible Redox-Dependent S-Nitrosylation of the Heart.

PloS one·2016
Same author

Differential role of S-nitrosylation and the NO-cGMP-PKG pathway in cardiac contractility.

Nitric oxide : biology and chemistry·2007
Same journal

Assessing the sustainability of reef and demersal fish stocks in Northwest México under a data-limited approach.

PeerJ·2026
Same journal

The impact of virtual reality exercise programs on postpartum pelvic pain and disability among women with lumbopelvic pain.

PeerJ·2026
Same journal

Soil salinity modulates fatty acid composition and antioxidant capacity of rice bran oil.

PeerJ·2026
Same journal

The optimal dose of brisk walking for improving blood pressure in hypertensive patients: a systematic review and bayesian meta-analysis of randomized controlled trials.

PeerJ·2026
Same journal

Enhanced sweet pepper yield through high-intensity artificial lighting and optimized plant density in high-latitude winter production.

PeerJ·2026
Same journal

Prenatal corticosteroid use improves the severity and complications of necrotizing enterocolitis in preterm infants: a retrospective multicenter clinical study in China.

PeerJ·2026
See all related articles

Related Experiment Video

Updated: Jan 23, 2026

Flying Insect Detection and Classification with Inexpensive Sensors
05:16

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

25.7K

One-class land-cover classification using MaxEnt: the effect of modelling parameterization on classification

Ignacio C Fernández1, Narkis S Morales1

  • 1Centro de Modelación y Monitoreo de Ecosistemas, Facultad de Ciencias, Universidad Mayor, Santiago, Chile.

Peerj
|June 11, 2019
PubMed
Summary
This summary is machine-generated.

Optimizing MaxEnt parameters is crucial for accurate one-class land-cover classification. Manual parameterization and careful threshold selection significantly improve results for various land covers, especially heterogeneous ones.

Keywords:
Land-coverLand-useMaximum entropyModel tuningRemote sensingUrban vegetation

More Related Videos

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

8.0K
Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

447

Related Experiment Videos

Last Updated: Jan 23, 2026

Flying Insect Detection and Classification with Inexpensive Sensors
05:16

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

25.7K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

8.0K
Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

447

Area of Science:

  • Remote Sensing and Geospatial Analysis
  • Machine Learning for Environmental Monitoring

Background:

  • Multiple-class land-cover classification is inefficient for single-class identification.
  • One-class classification algorithms offer a more efficient alternative.
  • MaxEnt is a promising algorithm, but its parameterization for land-cover classification is understudied.

Purpose of the Study:

  • To investigate how MaxEnt parameterization impacts land-cover classification accuracy.
  • To compare manual MaxEnt parameterization against default settings for four land covers in Santiago de Chile.
  • To identify key parameters influencing classification performance.

Main Methods:

  • Systematic evaluation of 25,344 MaxEnt classification maps by varying feature restrictions, regularization multipliers, sample sizes, training/testing proportions, and thresholds.
  • Assessment of classification accuracy using kappa values for built-up, irrigated grass, evergreen trees, and deciduous trees.
  • Analysis of the influence of parameter settings, particularly threshold selection and sample size, on classification outcomes.

Main Results:

  • MaxEnt achieved high kappa values (0.68-0.89) with optimal parameterization, varying by land-cover type.
  • Manual parameterization generally improved accuracy, with threshold selection being the most critical factor.
  • Model complexity influenced accuracy: simpler models for homogenous covers, complex models for heterogeneous covers. Sample size showed diminishing returns after 60 points.

Conclusions:

  • Effective MaxEnt parameterization, especially threshold selection, is vital for reliable one-class land-cover classification.
  • Manual tuning of parameters and thresholds is recommended to achieve satisfactory accuracy metrics.
  • MaxEnt demonstrates significant potential for one-class classification when settings are well understood and optimized.