Essays about: "Gaussian Mixture Models Cluster Analysis"
Showing result 1 - 5 of 6 essays containing the words Gaussian Mixture Models Cluster Analysis.
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1. Exploring Greenhouse Gas Emissions and socio-economic factors for climate change mitigation: A worldwide clustering analysis
University essay from Lunds universitet/Nationalekonomiska institutionen; Lunds universitet/Statistiska institutionenAbstract : In response to the pressing need to address climate change and reduce global greenhouse gas (GHG) emissions, this study implemented Gaussian Mixture Models Clustering to detect the levels of GHG emissions and related socio-economic factors in 174 countries. To handle the panel data, Principal Component Analysis was conducted to achieve dimension reduction. READ MORE
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2. Unsupervised Anomaly Detection and Root Cause Analysis in HFC Networks : A Clustering Approach
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Following the significant transition from the traditional production industry to an informationbased economy, the telecommunications industry was faced with an explosion of innovation, resulting in a continuous change in user behaviour. The industry has made efforts to adapt to a more datadriven future, which has given rise to larger and more complex systems. READ MORE
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3. Tick data clustering analysis establishing support and resistance levels of the EUR-USD exchange market
University essay from Lunds universitet/Matematisk statistikAbstract : Our aim is to use clustering algorithms in order to compute support and resistance levels within an intra-day trading setting. To achieve this we use a tick data set from the EUR-USD exchange market during 2019 as a measure of market activity. READ MORE
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4. Hierarchical Clustering of Time Series using Gaussian Mixture Models and Variational Autoencoders
University essay from Lunds universitet/Matematisk statistikAbstract : This thesis proposes a hierarchical clustering algorithm for time series, comprised of a variational autoencoder to compress the series and a Gaussian mixture model to merge them into an appropriate cluster hierarchy. This approach is motivated by the autoencoders good results in dimensionality reduction tasks and by the likelihood framework given by the Gaussian mixture model. READ MORE
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5. Customer segmentation of retail chain customers using cluster analysis
University essay from KTH/Matematisk statistikAbstract : In this thesis, cluster analysis was applied to data comprising of customer spending habits at a retail chain in order to perform customer segmentation. The method used was a two-step cluster procedure in which the first step consisted of feature engineering, a square root transformation of the data in order to handle big spenders in the data set and finally principal component analysis in order to reduce the dimensionality of the data set. READ MORE