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clustering-analysis

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A comprehensive bundle of utilities for the estimation of probability of informed trading models: original PIN in Easley and O'Hara (1992) and Easley et al. (1996); Multilayer PIN (MPIN) in Ersan (2016); Adjusted PIN (AdjPIN) in Duarte and Young (2009); and volume-synchronized PIN (VPIN) in Easley et al. (2011, 2012). Implementations of various …

  • Updated Oct 22, 2024
  • R

The Clusters-Features package allows data science users to compute high-level linear algebra operations on any type of data set. It computes approximatively 40 internal evaluation scores such as Davies-Bouldin Index, C Index, Dunn and its Generalized Indexes and many more ! Other features are also available to evaluate the clustering quality.

  • Updated Apr 1, 2022
  • Python

It is One of the Easiest Problems in Data Science to Detect the MNIST Numbers, Using a Classification Algorithm, Here I have used a csv File which contains the Pixels of the Numbers from 0 to 9 and we have to Classify the Numbers Accordingly. I have Used K-Means Classification Algorithm.

  • Updated Aug 19, 2019
  • HTML

🔎Data Understanding, Visualization , Preparation & Cleaning - Clustering algorithms (unsupervised learning) - Classification algorithms (supervised learning) - Sequential Pattern Mining

  • Updated Jan 19, 2021
  • Jupyter Notebook

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