Classification K-Means

-
K-Means est un algorithme de classification non supervisé car le nombre de classes est inconnu, la recherche de classes sera faite à l'aveugle.
Ce type de classification est facile à implémenter et à comprendre, le but ultime de cet algorithme est de regrouper les points selon un critère bien déterminé,  en effet l'entrée est un ensemble k groupes (clusters).
Par la suite on vise à calculer la distance entre chaque individu (point) et les k centre, qui sont déjà choisis au début. la plus petite distance est retenue pour inclure cet individu dans le groupe ayant le centre le plus proche.
Une fois tous les individus groupés, on aura k sous-nuages disjoints de la marge total pour chaque groupe, l'algorithme calcule des nouveaux centres de gravité
l'algorithme s’arrête lorsque les groupes construits deviennent stables
Attention :

Le défaut de la méthode c'est qu'on est obligé de fixer le K, aussi le résultat est fortement couplé avec les centres initiaux

J'aime bien expliquer le fonctionnement de cet algorithme par le schéma suivant :

le résultat de l'algorithme est d'avoir un groupement de points regroupés au tour d'un centre de gravité



Vous pouvez télécharger mon nouveau plugin sur NuGet en version 1.0.0

PM>Install-Package K-Means -Version 1.0.0




Commentaires

Enregistrer un commentaire

Posts les plus consultés de ce blog

Naive Bayes Classification Algorithm

-
Image
You are a data scientist,  an Intelligence Artificielle engineer, or a Statisticien, this post can help you to resolve your problems You are working on a classification problem and you have generated your set of hypothesis, created features and discussed the importance of variables. Within an hour, stakeholders want to see the first cut of the model. What will you do? You have hunderds of thousands of data points and quite a few variables in your training data set. In such situation, if I were at your place, I would have used ‘Naive Bayes‘, which can be extremely fast relative to other classification algorithms. It works on Bayes theorem of probability to predict the class of unknown data set. You wold like to know haw it work ? Step 1: Convert the data set into a frequency table Step 2: Create Likelihood table by finding the probabilities like Overcast probability = 0.29 and probability of playing is 0.64. Step 3: Naive Bayesian equation to calculate...
Lire la suite

Cross-Origin Resource Sharing and Azure Machine Learning web services

-
Image
Cross-Origin Resource Sharing (CORS) is a mechanism that allows web objects (e.g., JavaScript) from one domain to request objects (web service requests) from another domain. Cross-origin requests initiated from scripts have been subject to restrictions primarily for security reasons. CORS provides a way for web servers to support cross-site access controls, which enable secure cross-site data transfers. At the time of this writing, it should be noted that Azure Machine Learning web services do not currently support CORS requests. See the following link for more information: https://social.msdn.microsoft.com/Forums/en-US/b6ddeb77-30e1-45b2-b7c1-eb4492142c0a/azure-ml-published-web-services-cross-origin-requests?forum=MachineLearning. This CORS restriction really means that if you wish to fully exploit Azure Machine Learning web services for deployment, testing, and production for a wide variety of (web) clients, you will need to host your own server-side applications. You basically hav...
Lire la suite

ChatBot

-
Image
How we   choose the bot framework ? If i talk about Microsoft. Essentially we have a single bot, is built and later rolled out to multiple canvasses without any further customization. Currently, the platform supports many channels (such as Facebook Messenger, Slack, SMS, email, Web Chat) including Microsoft’s own premiers (like Skype, Cortana, Microsoft Teams, Bing, GroupMe). All settings are pre-configured on the Developer Portal with an easy-to-follow walkthrough about how to integrate the bot with the hosting applications. How we   consume the bot framework ? Developers can connect directly from their client application, web chat controls or mobile apps throw Direct Line REST API tool of the bot Connector. This API makes it possible to empower existing applications and services with a conversational user interface. Microsoft has its own massive range of cloud-based Cognitive Services   APIs with the power of machine learning and AI algorithms. ...
Lire la suite