Essays about: "multilabel classification"
Found 4 essays containing the words multilabel classification.
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1. Topical Classification of Images in Wikipedia : Development of topical classification models followed by a study of the visual content of Wikipedia
University essay from Linköpings universitet/DatorseendeAbstract : With over 53 million articles and 11 million images, Wikipedia is the greatest encyclopedia in history. The number of users is equally significant, with daily views surpassing 1 billion. Such an enormous system needs automation of tasks to make it possible for the volunteers to maintain. READ MORE
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2. Multilabel text classification of public procurements using deep learning intent detection
University essay from KTH/Matematisk statistikAbstract : Textual data is one of the most widespread forms of data and the amount of such data available in the world increases at a rapid rate. Text can be understood as either a sequence of characters or words, where the latter approach is the most common. READ MORE
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3. Comparing Feature Extraction Methods and Effects of Pre-Processing Methods for Multi-Label Classification of Textual Data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis aims to investigate how different feature extraction methods applied to textual data affect the results of multi-label classification. Two different Bag of Words extraction methods are used, specifically the Count Vector and the TF-IDF approaches. A word embedding method is also investigated, called the GloVe extraction method. READ MORE
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4. MLID : A multilabelextension of the ID3 algorithm
University essay from Blekinge Tekniska Högskola/Institutionen för programvaruteknik; Blekinge Tekniska Högskola/Institutionen för programvaruteknikAbstract : AbstractMachine learning is a subfield within artificial intelligence that revolves around constructingalgorithms that can learn from, and make predictions on data. Instead of following strict andstatic instruction, the system operates by adapting and learning from input data in order tomake predictions and decisions. READ MORE
