Refactor implementation

Question

I'm refactoring a C++ code doing kmean clustering. There are two version of the code:

Normal kmean
Feature aligned clustering: use slightly different distance metric and update rule.

How should I implement this effectively? Method overloading (this doesn't depend on input though)

OK so this is the pseudocode doing kmean clustering. I need to implement two versions of distance and update function.

int* kmean_clustering(vector<double[10]> data)
// each row of data hold one data point
// so we have M data points of 10 dimension
{
    // Split codebook
    // Assignment step
    Find the closest codebook based on distance(distance here can be Euclidean, Mahalanobis, .....)
    //Update step
}

Can you post some code, oterwise how can we suggest how to refector it? — lockstock
– lockstock, Commented Feb 26, 2013 at 23:48
Is function pointer a good idea? I don't want to have Kmean_Euclidean, Kmean_Mahalanobis, Kmean_blah_blah functions — Dzung Nguyen
– Dzung Nguyen, Commented Feb 27, 2013 at 23:20

Arun · Accepted Answer · 2013-02-27 02:20:26Z

2

A well written code is like reading a good novel. That's why Knuth calls it as an art of programming. This book might teach you bottom-up approach of refactoring.

answered Feb 27, 2013 at 2:20

Arun

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