Essays about: "classification with data imbalance"
Showing result 16 - 20 of 39 essays containing the words classification with data imbalance.
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16. Deep Learning for Driver Sleepiness Classification using Bioelectrical Signals and Karolinska Sleepiness Scale
University essay from Linköpings universitet/Institutionen för medicinsk teknikAbstract : Driver sleepiness contributes to a large amount of all road traffic crashes. Developing an objective measurement of driver sleepiness in order to prevent eventual traffic accidents is desirable. READ MORE
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17. Instance Segmentation of Multiclass Litter and Imbalanced Dataset Handling : A Deep Learning Model Comparison
University essay from Linköpings universitet/DatorseendeAbstract : Instance segmentation has a great potential for improving the current state of littering by autonomously detecting and segmenting different categories of litter. With this information, litter could, for example, be geotagged to aid litter pickers or to give precise locational information to unmanned vehicles for autonomous litter collection. READ MORE
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18. Flight Sorting Algorithm Based on Users’ Behaviour
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The model predicts the best flight order and recommend best flight to users. The thesis could be divided into the following three parts: Feature choosing, data-preprocessing, and various algorithms experiment. READ MORE
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19. Prediction of Lead Conversion With Imbalanced Data : A method based on Predictive Lead Scoring
University essay from Linköpings universitet/Statistik och maskininlärningAbstract : An ongoing challenge for most businesses is to filter out potential customers from their audience. This thesis proposes a method that takes advantage of user data to classify po- tential customers from random visitors to a website. READ MORE
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20. Machine Learning Applied to Reach Classification in a Northern Sweden Catchment
University essay from Umeå universitet/Institutionen för ekologi, miljö och geovetenskapAbstract : An accurate fine resolution classification of river systems positively impacts the process of assessment and monitoring of water courses, as stressed by the European Commission’s Water Framework Directive. Being able to attribute classes using remotely obtained data can be advantageous to perform extensive classification of reaches without the use of field work, with some methods also allowing to identify which features best described each of the process domains. READ MORE