Essays about: "clustering"
Showing result 1 - 5 of 557 essays containing the word clustering.
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1. Anomaly Detection in Log Files Using Machine Learning Techniques
University essay from Blekinge Tekniska Högskola/Fakulteten för datavetenskaperAbstract : Context: Log files are produced in most larger computer systems today which contain highly valuable information about the behavior of the system and thus they are consulted fairly often in order to analyze behavioral aspects of the system. Because of the very high number of log entries produced in some systems, it is however extremely difficult to seek out relevant information in these files. READ MORE
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2. Semantic Topic Modeling and Trend Analysis
University essay from Linköpings universitet/Statistik och maskininlärningAbstract : This thesis focuses on finding an end-to-end unsupervised solution to solve a two-step problem of extracting semantically meaningful topics and trend analysis of these topics from a large temporal text corpus. To achieve this, the focus is on using the latest develop- ments in Natural Language Processing (NLP) related to pre-trained language models like Google’s Bidirectional Encoder Representations for Transformers (BERT) and other BERT based models. READ MORE
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3. Clustering of Financial Account Time Series Using Self Organizing Maps
University essay from KTH/Matematisk statistikAbstract : This thesis aims to cluster financial account time series by extracting global features from the time series and by using two different dimensionality reduction methods, Kohonen Self Organizing Maps and principal component analysis, to cluster the set of the time series by using K-means. The results are then used to further cluster a set of financial services provided by a financial institution, to determine if it is possible to find a set of services which coincide with the time series clusters. READ MORE
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4. Experiments in speaker diarization using speaker vectors
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Speaker Diarization is the task of determining ‘who spoke when?’ in an audio or video recording that contains an unknown amount of speech and also an unknown number of speakers. It has emerged as an increasingly important and dedicated domain of speech research. READ MORE
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5. Clustering and Classification of Time Series in Real-Time Strategy Games - A machine learning approach for mapping StarCraft II games to clusters of game state time series while limited by fog of war
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : Real-time strategy (RTS) games feature vast action spaces and incomplete information,thus requiring lengthy training times for AI-agents to master them at the level of ahuman expert. Based on the inherent complexity and the strategical interplay betweenthe players of an RTS game, it is hypothesized that data sets of played games exhibitclustering properties as a result of the actions made by the players. READ MORE
