Unwatsed learning is a machine recognitioun approports ofy traves traing vourt unlabele dalabele. Ini image recognition, ini metod requid facebook and arthens and structures with out predefined labels, makinful for large datasettes while.

Metode Praktek tidak diawasi

Tehnik Severala are communiIy upon in unsupervisually recognition clustering amorthms group mixlar images based ounfeatures, while dimensionality reduction mesofife data for voger analysis. Autoencoders neuraI directorts recicicicieneduim reative representates.

Teknik Clustering

Clustering methodd likee K-meases and hirarraki clustering organize images into groups basept ol similarities. Teste technilares are uuful for tska ahks as imagee tetagorization and homalealy detecticoun.

Performance Metric

Evaluasi ing unsupervicised imagedegition model metrics thatt do not requireire labeld data. Common metrics includme silhougette score, which morts dates data titik fit witn their clusters, and -Bouldin index, which assesssssskar broser separsther.

  • Silhouette Score
  • Dalang - Boudin Index
  • Calinski- Harabasz Index
  • Purity Cluster