Essays about: "K-means algorithm"
Showing result 11 - 15 of 107 essays containing the words K-means algorithm.
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11. Initialization of the k-means algorithm : A comparison of three methods
University essay from Stockholms universitet/Matematiska institutionenAbstract : k-means is a simple and flexible clustering algorithm that has remained in common use for 50+ years. In this thesis, we discuss the algorithm in general, its advantages, weaknesses and how its ability to locate clusters can be enhanced with a suitable initialization method. READ MORE
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12. Quantification of the Performance of Algorithms for spectra Baseline Correction
University essay from Lunds universitet/Fysiska institutionen; Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisationAbstract : Spectroscopy serves as a vital tool in both scientific research and industrial applications. In spectral analysis, baseline correction is important in order to be able to efficiently extract essential features. READ MORE
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13. Design of high performance buildings : Vulnerability of buildings to climate change from an energy perspective
University essay from KTH/Hållbara byggnaderAbstract : The challenge of climate change is twofold: to mitigate (prevent) the causes of climate change and to prepare (adapt) to the inevitable effects and consequences. Building and construction are key sectors for decarbonisation (mitigation). READ MORE
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14. A treemap-based interactive clustering algorithm
University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013); Karlstads universitet/Avdelningen för datavetenskapAbstract : In this thesis, a treemap-based interactive clustering algorithm is implemented and evaluated. The treemap's rectangles present scatterplots of dimensionally reduced renderings of clusters. READ MORE
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15. Comparison of initialization methods of K-means clustering for small data
University essay from Uppsala universitet/Statistiska institutionenAbstract : Clustering of observations into groups arises as a fundamental challenge both in academia and industry. Many clustering algorithms exist, and the most widely used clustering algorithm, the K-means, notably suffers from sensitivity to initial allocation of cluster centers. READ MORE