Topic: "mini-batch-kmeans"
mlampros/ClusterR
Gaussian mixture models, k-means, mini-batch-kmeans and k-medoids clustering
Language: R - Size: 2.53 MB - Last synced at: 2 days ago - Pushed at: 11 months ago - Stars: 85 - Forks: 29
mlampros/SuperpixelImageSegmentation
Image Segmentation using Superpixels, Affinity Propagation and Kmeans Clustering
Language: R - Size: 339 KB - Last synced at: about 1 month ago - Pushed at: almost 2 years ago - Stars: 20 - Forks: 6
SalamanderXing/jax-min-batch-kmeans
Jax implementation of Mini-batch K-Means algorithm
Language: Python - Size: 10.7 KB - Last synced at: 3 days ago - Pushed at: over 2 years ago - Stars: 4 - Forks: 0
wlzhao22/xkmeans
This is an implementation about the k-means and a dozens of its variants.
Language: C++ - Size: 282 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0
Scrayil/k-means
This project consists in the implementation of the K-Means and Mini-Batch K-Means clustering algorithms. This is not to be considered as the final and most efficient algorithm implementation as the objective here is to make a clear omparison between the sequential and parallel execution of the clustering steps.
Language: C++ - Size: 29.1 MB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0
boosuro/image_color_compression_kmeans
Color compression of an image with K-Means Clustering Algorithm which can help in devices with low processing power and memory for large images
Language: Jupyter Notebook - Size: 2.15 MB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 0
zoppellarielena/Mini-Batch-K-means-on-RCV1-dataset-using-Dask
Developed for "Management and Analysis of Physics Dataset Mod. B," this project uses Dask and CloudVeneto VMs to handle a massive 250GB dataset. Clustering on 800k RCV1 articles involves dataset reduction by macrocategory and also implementing cosine similarity for improved clustering, as suggested by Natural Language Processing principles.
Language: HTML - Size: 38.5 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
msikorski93/Seed-Clustering
Performing basic clustering on a seeds dataset.
Language: Jupyter Notebook - Size: 929 KB - Last synced at: 3 months ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
cbrightly1/fnb-customer-segmentation
This project used a Kmeans after PCA model to segment retail customers to optimize marketing efforts. When the model repeatedly returned a single cluster, the model was used to prove the customers' homogenous characteristics. Influenced the bank's marketing strategies and initiatives. Developed in Jupyter Notebook with Python for FNB.
Language: Jupyter Notebook - Size: 380 KB - Last synced at: 3 months ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0
