// multi-utility computation suite · offline · instant · precise
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cs.k-means-optimal-clusters Calculator
Estimates the optimal number of k-means clusters using the elbow method from within-cluster sum of squares at each k value. The 'elbow' is where the marginal reduction in within-cluster variance stops being worth adding another cluster.
Inputs
Total Variance
The square of standard deviation. Less intuitive than SD (units are squared), but used in many statistical formulas.
Within Cluster K2
The square of standard deviation. Less intuitive than SD (units are squared), but used in many statistical formulas.
Within Cluster K3
The square of standard deviation. Less intuitive than SD (units are squared), but used in many statistical formulas.
Within Cluster K4
The square of standard deviation. Less intuitive than SD (units are squared), but used in many statistical formulas.