Uniform Manifold Approximation and Projection (UMAP):Another dimensionality reduction technique similar to t-SNE, often faster and preserving both local and global structures in the data. 6. Clustering and Segmentation: DBSCAN:A clustering algorithm called Density-Based Spatial Clustering of Applications w...
What is Data Normalization in Vector Databases? Data normalization in vector databases involves adjusting vectors to a uniform scale, a critical step for ensuring consistent performance in distance-based operations, such as clustering or nearest-neighbor searches. Common techniques like min-max scaling,...
but they have different goals and methods. PCA is used to reduce the dimensionality of the data, while k-means clustering groups data points together based on similarity. The technique you select depends on the specific dataset and goals of your analysis. ...
The clustering approaches cannot work well in such cases. Hence, in this paper, we cast the alias-disambiguation step as a pairwise classification problem. The supervised approaches usual- ly outperforms unsupervised approaches in entity resolution tasks [9, 26]. However, it is expensive to ...
What is Data Normalization in Vector Databases? Data normalization in vector databases involves adjusting vectors to a uniform scale, a critical step for ensuring consistent performance in distance-based operations, such as clustering or nearest-neighbor searches. Common techniques like min-max scaling,...
PCA and k-means clustering are both unsupervised machine learning techniques used for data analysis, but they have different goals and methods. PCA is used to reduce the dimensionality of the data, while k-means clustering groups data points together based on similarity. The technique you select ...
What is Data Normalization in Vector Databases? Data normalization in vector databases involves adjusting vectors to a uniform scale, a critical step for ensuring consistent performance in distance-based operations, such as clustering or nearest-neighbor searches. Common techniques like min-max scaling...
What is Data Normalization in Vector Databases? Data normalization in vector databases involves adjusting vectors to a uniform scale, a critical step for ensuring consistent performance in distance-based operations, such as clustering or nearest-neighbor searches. Common techniques like min-max scaling,...