How Predicting The Academic Success of Students of the ESPAM MFL?: A Preliminary Decision Trees Based Study

Carrillo, Jéssica Morales; Parraga-Alava, Jorge

doi:10.1109/etcm.2018.8580296

Cited by 5 publications

(1 citation statement)

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“…Meanwhile, classification aims finding a class to which an item belongs as from patterns in a labeled data set. Here, methods as artificial neural networks, SVM (Support Vector Machine) and decision trees have been used to perform classification tasks [5], [6], [7].…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

RoCoLe: A robusta coffee leaf images dataset for evaluation of machine learning based methods in plant diseases recognition

et al. 2019

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In this article we introduce a robusta coffee leaf images dataset called RoCoLe. The dataset contains 1560 leaf images with visible red mites and spots (denoting coffee leaf rust presence) for infection cases and images without such structures for healthy cases. In addition, the data set includes annotations regarding objects (leaves), state (healthy and unhealthy) and the severity of disease (leaf area with spots). Images were all obtained in real-world conditions in the same coffee plants field using a smartphone camera. RoCoLe data set facilitates the evaluation of the performance of machine learning algorithms used in image segmentation and classification problems related to plant diseases recognition. The current dataset is freely and publicly available at https://doi.org/10.17632/c5yvn32dzg.2 .

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Section: Experimental Design Materials and Methodsmentioning

confidence: 99%