Sentence examples for cut height from inspiring English sources

Cut height optimization: ground truth clusters are used in combination with the Rand index to identify the optimal clustering cut height for each input attribute.

We first describe two approaches for automatically selecting cut heights for agglomerative clustering: dynamic cut height, which is unsupervised, and optimized cut height, which is supervised.

Using optimized cut height, the best choice is found using the Rand index as a performance measure for each possible cut height parameter value from 0.01 to 0.99.

The optimized cut height was identified by empirically testing cut height values between 0.01 and 0.99 in increments of 0.01 against the training data.

We can see that our 'best min optimized cut height' approach performs best.

Traditionally, a static cut height is selected based on the type of data being clustered.

Figure 3 Rand index values for each input attribute at various cut heights.

Once the training dataset was complete, Rand index optimized cut heights and top performing individual or combined input attributes would be selected using the training data.

Because website input attributes can have very different similarities and still be related, we deploy two methods for automatically selecting the optimal cut heights, one unsupervised and one supervised.

Finally, the cut heights selected during the training phase are used to perform optimized combined clustering against the testing data to assess how this technique might perform in the real-world setting previously described above.

Going forward, the optimized cut heights would be used during optimized combined-clustering to cluster all new websites identified using the top performing individual or combined input attribute matrices.