An implementation of K-Means algorithm in R
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Updated
Dec 26, 2013 - R
An implementation of K-Means algorithm in R
Data Mining Matlab files used as part of a class on Data Mining taught as part of the MSc. Data Science (2014) at Lancaster University.
Clustering toy datasets using K-means algorithm and Spectral Clusting algorithm
The most common algorithm uses an iterative refinement technique. Due to its ubiquity it is often called the k-means algorithm; it is also referred to as Lloyd's algorithm, particularly in the computer science community.
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A collection of Unsupervised Machine Learning algorithms in Ruby
Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means
Implement the K-means unsupervised learning algorithm. Utilized the simplified Iris dataset to test code.
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K-Mean clustering program in Java to cluster the data point into 4 clusters
2D k-means Python 2.7 module implemented in pure C
K-Means++ Clustering using Gap Statistic for determining optimal value of K in Python
Machine learning using python
Some basic classification methods (Naive Bayes, Decision Trees, Nearest Neighbour, Perceptrons) implemented from scratch in Java
This is code for make classification using K-Means Method in Java
A Java program for clustering data with the k-means algorithm.
Data clustering algorithms implemented in Java with Strategy design pattern.
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