首页|Researcher from Warsaw University of Technology Reports Recent Findings in Machi ne Learning (Comparative analysis of the performance of selected machine learnin g algorithms depending on the size of the training sample)
Researcher from Warsaw University of Technology Reports Recent Findings in Machi ne Learning (Comparative analysis of the performance of selected machine learnin g algorithms depending on the size of the training sample)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in artificial intelligence. According to news reporting originating from Warsaw, Poland, by Ne wsRx correspondents, research stated, “The article presents an analysis of the e ffectiveness of selected machine learning methods: Random Forest (RF), Extreme G radient Boosting (XGB), and Support Vector Machine (SVM) in the classification o f land use and cover in satellite images.” Our news correspondents obtained a quote from the research from Warsaw Universit y of Technology: “Several variants of each algorithm were tested, adopting diffe rent parameters typical for each of them. Each variant was classified multiple ( 20) times, using training samples of different sizes: from 100 pixels to 200,000 pixels. The tests were conducted independently on 3 Sentinel-2 satellite images , identifying 5 basic land cover classes: built-up areas, soil, forest, water, and low vegetation. Typical metrics were used for the accuracy assessment: Cohen’s kappa coefficie nt, overall accuracy (for whole images), as well as F-1 score, precision, and re call (for individual classes). The results obtained for different images were co nsistent and clearly indicated an increase in classification accuracy with the i ncrease in the size of the training sample.”
Warsaw University of TechnologyWarsawPolandEuropeAlgorithmsCyborgsEmerging TechnologiesMachine LearningS upport Vector Machines
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