Sökning: "Kmeans"

Visar resultat 1 - 5 av 15 uppsatser innehållade ordet Kmeans.

1. 1. Domain Knowledge and Representation Learning for Centroid Initialization in Text Clustering with k-Means : An exploratory study

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :David Yu; [2023]
   Nyckelord :Natural language processing; Sentiment analysis; Clustering; Language model; Transformer; Heuristic; Språkteknologi; Sentimentanalys; Klustering; Språkmodell; Transformer; Heuristik;

   Sammanfattning : Text clustering is a problem where texts are partitioned into homogeneous clusters, such as partitioning them based on their sentiment value. Two techniques to address the problem are representation learning, in particular language representation models, and clustering algorithms. LÄS MER

3. 2. Evaluation of Machine Learning techniques for Master Data Management

   Magister-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi

   Författare :Fatime Toçi; [2023]
   Nyckelord :Master Data Management; Machine Learning; data quality; data duplicates;

   Sammanfattning : In organisations, duplicate customer master data present a recurring problem. Duplicate records can result in errors, complication, and inefficiency since they frequently result from dissimilar systems or inadequate data integration. LÄS MER

4. 3. Advancing Keyword Clustering Techniques: A Comparative Exploration of Supervised and Unsupervised Methods : Investigating the Effectiveness and Performance of Supervised and Unsupervised Methods with Sentence Embeddings

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Filippo Caliò; [2023]
   Nyckelord :Keyword Clustering; Supervised Learning; Unsupervised Learning; Cluster Labels; Natural Language Processing; Sentence Embeddings; Nyckelord Klustring; övervakad inlärning; oövervakad inlärning; klustermärkning; naturlig språkbehandling; Inbäddning av meningar;

   Sammanfattning : Clustering keywords is an important Natural Language Processing task that can be adopted by several businesses since it helps to organize and group related keywords together. By clustering keywords, businesses can better understand the topics their customers are interested in. LÄS MER

5. 4. A Case Study: Optimising PAP ambulance location with data and travel time analysis

   Master-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)

   Författare :Kurasinski Lukas; Tan Jason; [2022]
   Nyckelord :Data science; PAP; ambulance; travel time analysis; machine learning; optimization; case study; mental illness; Region skane; psychiatric ambulance; prehospital acute psychiatry; clustering; kmeans; regression; population coverage; area coverage; response time; ambulance station; data analysis;

   Sammanfattning : The mental health concerns in Sweden have been increasing since the beginning of the 2000’s, where Skåne County in the southern parts of Sweden has shown to be slightly higher in a proportion of reported cases in comparison to other regions. To address the growing need for psychiatric healthcare, the health services of the region of Skåne (Region Skåne) have introduced a psychiatric ambulance unit as a part of first responders. LÄS MER

7. 5. Comparison of initialization methods of K-means clustering for small data

   Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Liam Tabibzadeh; [2022]
   Nyckelord :Statistics; Clustering; K-means; Hierarchical; Initialization method; Simulation; Experiment; Factorial Design; Monte Carlo Simulation; Monte Carlo; Data; Classification; Cluster Analysis; R;

   Sammanfattning : 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. LÄS MER