Need to implement k-means in java for customer classification . customers buy products from shop . they will pay while they buying , pay at the end of the month , some customers will take time to pay . some customers dont pay at all . have to classify using k-means algorithm .
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...stack (numpy, pandas, matplotlib). My script uses k-means clustering and uses distortion method to find the optimal number of clusters for a given set of data points. It is a direct implementation of the post from this blog: [url removed, login to view] , however with all the errors fixed
My algorithm will basically does the following: Keywords : spark, python,scala,machine learning 1) Run k-means on the initial data. 1.1) show the clusters 2) Select the k centroids 3) Update instances of the dataset for the incoming new data 4) Apply Core Based Incremental Algorithm: 4.1) show the new clusters with the metrics and we need
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Its based on Clustering i.e. Data mining especially doing calculations using K-means Algorithm. The data set is provided and need to write R codes. Need to be familiar with how to determine SSE, SSB, TSS, clusters and centroid values
Implement K-means parallel algorithm using MPI+OpenMP+CUDA in pure C language.
...velocity (vxi, vyi) are known for each point Pi. Its position at the given time t can be calculated as follows: xi(t) = xi + t*vxi yi(t) = yi + t*vyi Implement simplified K-Means algorithm to find K clusters. Find a first occurrence during given time interval [0, T] when a system of K clusters has a Quality Measure q that is less than given value QM