Difference between revisions of "Hierarchical Cluster Analysis (HCA)"
m (Text replacement - "http:" to "https:") |
m |
||
| Line 2: | Line 2: | ||
|title=PRIMO.ai | |title=PRIMO.ai | ||
|titlemode=append | |titlemode=append | ||
| − | |keywords=artificial, intelligence, machine, learning, models | + | |keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools |
| − | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | + | |
| + | <!-- Google tag (gtag.js) --> | ||
| + | <script async src="https://www.googletagmanager.com/gtag/js?id=G-4GCWLBVJ7T"></script> | ||
| + | <script> | ||
| + | window.dataLayer = window.dataLayer || []; | ||
| + | function gtag(){dataLayer.push(arguments);} | ||
| + | gtag('js', new Date()); | ||
| + | |||
| + | gtag('config', 'G-4GCWLBVJ7T'); | ||
| + | </script> | ||
}} | }} | ||
[https://www.youtube.com/results?search_query=Hierarchical+Cluster+Analysis+HCA YouTube search...] | [https://www.youtube.com/results?search_query=Hierarchical+Cluster+Analysis+HCA YouTube search...] | ||
| Line 10: | Line 19: | ||
* [[Hierarchical Clustering; Agglomerative (HAC) & Divisive (HDC)]] | * [[Hierarchical Clustering; Agglomerative (HAC) & Divisive (HDC)]] | ||
* [[Hierarchical Temporal Memory (HTM)]] | * [[Hierarchical Temporal Memory (HTM)]] | ||
| − | |||
* [[...find outliers]] | * [[...find outliers]] | ||
* [[Clustering]] | * [[Clustering]] | ||
Revision as of 13:00, 2 July 2023
YouTube search... ...Google search
- Hierarchical Clustering; Agglomerative (HAC) & Divisive (HDC)
- Hierarchical Temporal Memory (HTM)
- ...find outliers
- Clustering
- Identify clusters (items) with closest distance
- Join them to new clusters
- Compute distance between clusters (items)
- Return to step 1
The HCPC (Hierarchical Clustering on Principal Components) approach allows us to combine the three standard methods used in multivariate data analyses (Husson, Josse, and J. 2010):
