============================= classification

Classification of N-dim data by Euclidean measure.

Introduction

Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). Classification assumes that the clusters have been predetermined and simply scans flows of multi-dimensional data points for being inside any of the given clusters. For anomaly detection, the clusters can be computed off-line over a large period of time, to specify clusters of normal or desired behavior, and then data points that lie outside of any known clusters, can be given special attention. Clustering in general is a main task of exploratory data mining, and a common technique for statistical data analysis, used in many fields, including machine learning, pattern recognition, image analysis, information retrieval, and bioinformatics.

Classification on AppGallery

Usage

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Features

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To-Do

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