Improving K-Medoids Clustering for Semantic Data
$10-30 USD
Pagado a la entrega
I'm facing an issue with my K-Medoids clustering. I have two phrases that share similar words, but are not similar as a whole, causing overlaps in the clustering process. I used Sentence-Transformers for semantic similarity and cosine distance for the distance measure.
The main goal is to increase the accuracy of the clustering. I'm open to suggestions for alternative clustering algorithms that could better handle this situation.
Ideal skills for this project include:
- Expertise in various clustering algorithms
- Proficiency in Python and familiar with the Sentence-Transformers library
- Strong understanding of semantic similarity and distance measures
- Experience in improving clustering processes and increasing accuracy.
Nº del proyecto: #39036769
Sobre el proyecto
14 freelancers están ofertando un promedio de $36 por este trabajo
Hi, I'm an experienced Python developer with the necessary skills to complete your project. I already worked on NLP project topics including skill sets: • Proficiency in Machine Learning techniques, deep networks (CNN, Más
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Hello, I am an automation and computer science engineer with extensive experience of 7 years in matlab/ simulink in machine learning, data processing, and clustering algorithms. I’ve worked with various clustering tec Más
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Hello dear client, I understand your challenge of clustering semantically similar phrases where partial word overlaps are causing issues. I am a highly skilled engineer with recent experience in advanced ML algorithms Más
Hi, I can help improve your K-Medoids clustering accuracy by addressing phrase overlap issues and exploring alternative clustering methods. How I Can Help: Optimize distance measures beyond cosine similarity for bet Más