ARDEEE RAYL·Nov 3How Data Mining DecidesWhat Is Close: Similarity, Dissimilarity and DistanceThe question underneath data mining. Almost every data mining technique, sooner or later, asks one deceptively simple question: how close…
Rosid Zahrul Kirom·Nov 2Is My Clustering Any Good? A Simple Walkthrough with Six PointsFrom distance to hierarchical clustering, DBSCAN and cluster validation
Krishna Kakatur·Oct 30Vector Similarity Metrics Explained: Dot Product, Cosine Similarity, and Euclidean DistanceVector similarity metrics like dot product, cosine similarity, and Euclidean distance measure different types of relationships between the…
Gollapalli Sai Teja·Oct 13K-Nearest Neighbors (KNN): A Practical Guide to Classification and RegressionLearn how the KNN algorithm works, understand distance metrics and feature scaling, and implement KNN classification and regression using…
InTowards AIbyLohith Prasanna Teja Kakumanu·Oct 2Understanding Similarity Measures / Metrics in Data ScienceI’m writing this blog to give you a quick glimpse of the Similarity Metrics that we use in industry covering about why we need them, when…A response icon3A response icon3
Nachiket Mehendale·Sep 29The Role of Magnitude in Euclidean Distance and Other Similarity Search MetricsCosine similarity is widely used in RAG pipelines to compare vectors. Euclidean distance (L2) can be a better fit when the magnitude of a…
InData And BeyondbyDima Iakubovskyi·Sep 17You Picked Euclidean Distance by Default, But It Was the Wrong ChoiceOn the same text data, tuning k bought 5.8 accuracy points, but switching the distance metric bought 20.8A response icon1A response icon1
Sathwik Pinninti·Jul 28K-Nearest Neighbours: Building a Fraud transaction detection Model from scratchI finally hit the next algorithm in my list which turned out to be quite a different one from all the ones we’ve learnt previously. Unlike…
Ashish Johnson·Jun 28L1 vs L2 Normalization Explained Like You’re Five (But Accurate Enough for ML Engineers)“I know the formulas. But I still don’t know what L1 and L2 normalization actually mean.”
