Analysing practical examples by using principal component analysis (PCA) and Clustring
-
Updated
May 14, 2024 - R
Analysing practical examples by using principal component analysis (PCA) and Clustring
Clusterização dos dados presentes no dataset de câncer de mama, implementando os algoritmos K-means, algoritmo do cotovelo (elbow method) e da silhueta média (Silhouette).
K-means as an unsupervised machine learning technique. Customer Segmentation Case.
Avaliação do estado de aplicativos Android entre os anos de 2010 e 2018 presentes na Google Play Store por técnicas de visualização de dados. Identificação de parâmetros potencialmente importantes para o número de instalações de um aplicativo e seu envolvimento com a precificação (gratuito ou pago), através do uso de técnicas de machine learning.
This is my first attempt at a KNN model, where I attempt to classify the purchase of caravan insurance in the Caravan data set (ISLR package).
Customer Segmentation using R
Grouping pupils according to the performance at two intermediate examinations
Repositorio creado para almacenar archivos, script y el informe final del curso de modelamiento estadístico del Diplomado en Big Data de la Pontificia Universidad Católica de Chile.
Classify the subsidy eligible users based on their electricity usage patterns
Clustering wedding guests.
Supervised and unsupervised analysis
Clustering personalities and labelling based on sampled survey responses (Hierarchical and K-Means).
Add a description, image, and links to the elbow-method topic page so that developers can more easily learn about it.
To associate your repository with the elbow-method topic, visit your repo's landing page and select "manage topics."