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All Blog Posts Tagged 'Clustering' (6)

US Arrests: Hierarchical Clustering using DIANA and AGNES

Introduction

Data Science and Machine Learning are furtive, they go un-noticed but are present in all ways possible and everywhere. They contribute significantly in all the fields they are applied and leave us with evidence which we can rely on and take data-driven directions. Today, a very interesting area we are going to see an example of Data Science and Machine Learning is ‘Crimes’. We are going to focus on types of crimes taken place across…

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Added by Neeraj on July 25, 2019 at 7:30am — No Comments

How Can Python Help Solve Machine Learning Challenges?

Summary: Python’s open-source and high-level nature, as well as its comprehensive libraries, make it the perfect fit to solve the numerous real-life ML challenges.

The increasing popularity and accessibility of Artificial Intelligence solutions is rapidly reshaping many industries, from healthcare through finance to aviation. Although the application of the latest technologies has always been an essential consideration for companies striving to get…

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Added by Łukasz Grzybowski on July 23, 2019 at 1:30am — No Comments

K Means Clustering Algorithm & its Application

What is K Means Clustering?

Clustering means grouping things which are similar or have features in common and so is the purpose of k-means clustering. K-means clustering is an unsupervised machine learning algorithm for clustering ‘n’ observations into ‘k’ clusters where k is predefined or user-defined constant. The main idea is to define k centroids, one for each cluster.

The K Means algorithm…

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Added by Muhammad Rizwan on September 27, 2018 at 7:06am — No Comments

From social media to public health surveillance: Word embedding based clustering method for twitter classification

Social media provide a low-cost alternative source for public health surveillance and health-related classification plays an important role to identify useful information. We summarized the recent classification methods using social media in public health. These methods rely on bag-of-words (BOW) model and have difficulty grasping the semantic meaning of texts. Unlike these methods, we present a word embedding based clustering method. Word embedding is one of the strongest trends in Natural…

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Added by CD on January 4, 2018 at 10:30am — 1 Comment

Find Marketing Clusters in 20 minutes in R

Have you ever wondered how to segment your customers? Customer segmentation is a really useful technique to group similar customers together and understand what works for that. You can then tailor your offering and marketing messages to the specific segments. If you do it right, you should be able to see a healthy increase in sales. After all, companies like Amazon target their customers on an individual level so you should at least be targeting them on a segment level.…

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Added by Sudhanshu Ahuja on April 2, 2016 at 10:34pm — 6 Comments

Clustering Similar Images Using MapReduce Style Feature Extraction with C# and R

Abstract



This article provides a full demo application using both the C# and R programming languages interchangeably to rapidly identify and cluster similar images.   The demo application includes a directory with 687 screenshots of webpages.  Many of these images are very similar with different domain names but near identical content.  Some images are only slightly similar with the sites using the same general layouts but different colors and different images on certain…

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Added by Jake Drew Ph.D. on June 25, 2014 at 4:00pm — No Comments

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