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@@ -122,8 +122,8 @@ const state = {
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};
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// Metrics
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-const getBestKMean = (stats, q) => argMin(stats.kMeans.map((z, i) => vectorDist(z.vector, q.vector) / stats.kWeights[i]));
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-const getWorstKMean = (stats, q) => argMax(stats.kMeans.map((z, i) => vectorDist(z.vector, q.vector) / stats.kWeights[i]));
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+const getBestKMean = (stats, q) => argMin(stats.kMeans.map(z => vectorDist(z.vector, q.vector)));
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+const getWorstKMean = (stats, q) => argMax(stats.kMeans.map(z => vectorDist(z.vector, q.vector)));
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const getScale = weight => state.includeScale ? (1 / weight) : 1;
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@@ -228,8 +228,8 @@ const mathDefinitions = {
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\pi_i &= \frac{\left|P_i\right|}{\left|P\right|} \\
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M\left(P\right) &= ${mathArgBest("max", "P_i")} \left( \left|P_i\right| \right) \\
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m\left(P\right) &= ${mathArgBest("min", "P_i")} \left( \left|P_i\right| \right) \\
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- \alpha\left(P\right) &= ${mathArgBest("min", "P_i")} \left[ \frac{1}{\pi_i} \left|\left| \vec{q} - \vec{\mu}\left(P_i\right) \right|\right| \right] \\
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- \omega\left(P\right) &= ${mathArgBest("max", "P_i")} \left[ \frac{1}{\pi_i} \left|\left| \vec{q} - \vec{\mu}\left(P_i\right) \right|\right| \right]
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+ \alpha\left(P\right) &= ${mathArgBest("min", "P_i")} \left( \left|\left| \vec{q} - \vec{\mu}\left(P_i\right) \right|\right| \right) \\
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+ \omega\left(P\right) &= ${mathArgBest("max", "P_i")} \left( \left|\left| \vec{q} - \vec{\mu}\left(P_i\right) \right|\right| \right)
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\end{aligned}
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`,
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};
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