Supervised classification
A comparison of supervised classification methods for the prediction of substrate type using multibeam acoustic and legacy grain-size data.
... Supervised classification techniques are algorithms that ‘learn’ patterns in data to predict an associated discrete ...data. Supervised machine learning techniques that have been trialled include ...
14
Detection and Evaluation of Cheating on College Exams using Supervised Classification
... a supervised classification algorithm was employed to create inference models capable to detect the presence and level of cheating in a real set of scholar ...
22
Synthesis of supervised classification algorithm using intelligent and statistical tools
... In this stage we worked with a large amount of samples from our data base with the same color classification parameters. We made the simulation of the network that is already created in the training stage. In the ...
9
J. Braz. Chem. Soc. vol.24 número3
... supervised classification PLS-DA models based on ATR-FTIR spectra. The aim was to develop a rapid and non-destructive tool for classifying the seized cocaine samples as a function of their chemical form and ...
11
An object based approach for coastline extraction from Quickbird multispectral images
... and supervised classification, segmentation, NDVI (Normalized Difference Vegetation Index) and NDWI (Normalized Difference Water Index) are only some of the methodological aspects that have been already ...
7
The application of FORMOSAT-2 high-temporal- and high-spatial resolution imagery for monitoring open straw burning and carbon emission detection
... of these being the greenhouse gases which cause global cli- mate change. In this study FORMOSAT-2 satellite images and ground-truth data from 2008 and 2009 are used to con- duct supervised classification ...
8
CLASSIFICATION ALGORITHMS FOR BIG DATA ANALYSIS, A MAP REDUCE APPROACH
... different classification methods, and major achievements have been made so ...perform supervised classification procedures on huge amounts of data, usually referred as big data, on a distributed ...
5
Classification of the financial sustainability of health insurance beneficiaries through data mining techniques
... The procedure used in this study is predominantly quantitative, using statistical analysis methods in accordance with the objectives. Data analysis began with descriptive and inferential statistical techniques. This was ...
14
USO DE IMAGENS MULTIESPECTRAIS ASTER PARA MAPEAR ESPÉCIES INVASORAS LENHOSAS NA RESERVA NATURAL DE PICO DA VARA (AÇORES, PORTUGAL)
... in supervised classification maps has been reached (especially when using MLC and KNN classifiers) by developing a classification scheme which includes the use of both VNIR and VNIR-SWIR ASTER ...
11
Definição dos níveis de conservação ambiental considerando a ocupação antrópica na área protegida da bacia hidrográfica do rio Uberaba
... the supervised classification to obtain the soil cover of the region and found that the human intervention was responsible for forest deforestation in ...the classification technique used in both was ...
13
Alien plant monitoring with ultralight airborne imaging spectroscopy.
... to supervised classification methods, ground- truthing is always a critical issue requiring considerable resources, and with a high potential impact on the end ...
9
Machine learning approach for the outcome prediction of temporal lobe epilepsy surgery.
... using supervised classification tech- ...the supervised class variable describes seizure free patients (n = 14) and those exhibiting an improvement only (n = ...
9
SPATIO-TEMPORAL DATA MODELING IN RESPONSE TO DEFORESTATION MONITORING
... these maps using ground data to measure the accuracy either using Kappa or overall accuracy index (Appendix B explains about these terminologies) in order to define the optimal c that can show the best change and no ...
79
Partially Supervised Approach in Signal Recognition
... of classification basically establishes a transformation F →D between the features and the ...as supervised classification (where the parameters of a classifier function D are ...the ...
12
Minimal Feature Set for Unsupervised Classification of Knee MR Images
... for classification process in next phase. Classification is implemented and performance of different parameters are compared using five algorithms ‘ID3’, ‘J48’, ‘FID3new’, ‘Naive Bayes’ & ...
6
Less rain, more water in ponds: a remote sensing study of the dynamics of surface waters from 1950 to present in pastoral Sahel (Gourma region, Mali)
... a classification based on pure pixels only may lead to a rough approximation of the effective pond’s surface for most ponds in the ...sub-pixel classification to refine the ...
16
Detecting portuguese and english Twitter users’ gender
... In this section we present the experiments and classifiers used to learn from the labelled datasets for each group of features and for the combined classifier. The purpose is to be able to classify a user outside of our ...
102
Virtual Calibration of Cosmic Ray Sensor: Using Supervised Ensemble Machine Learning
... of supervised machine learning methods has been investigated to virtually and dynamically calibrate the cosmic ray sensors measuring area wise bulk soil ...four supervised estimators, namely Sugano type ...
7
Educ. rev. vol.32 número2
... However, it is worth return, from different perspectives, to the case of practice as a curricular component and of supervised curricular teaching practicum. These components have been understood, by oficial ...
26
A systematic comparison of supervised classifiers.
... Many comparative studies are specific to a given problem or task. Perhaps this is a consequence of the ‘‘No Free Lunch theorem’’, which states that, without any prior, no single method can be preferred [32–34]. A ...
14