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  2. Elbow method (clustering) - Wikipedia

    en.wikipedia.org/wiki/Elbow_method_(clustering)

    The idea is that the first clusters will add much information (explain a lot of variation), since the data actually consist of that many groups (so these clusters are necessary), but once the number of clusters exceeds the actual number of groups in the data, the added information will drop sharply, because it is just subdividing the actual groups.

  3. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Mark cell ‘c’ as a new cluster; Calculate the density of all the neighbors of ‘c’ If the density of a neighboring cell is greater than threshold density then, add the cell in the cluster and repeat steps 4.2 and 4.3 till there is no neighbor with a density greater than threshold density. Repeat steps 2,3 and 4 till all the cells are ...

  4. Single-linkage clustering - Wikipedia

    en.wikipedia.org/wiki/Single-linkage_clustering

    The function used to determine the distance between two clusters, known as the linkage function, is what differentiates the agglomerative clustering methods. In single-linkage clustering, the distance between two clusters is determined by a single pair of elements: those two elements (one in each cluster) that are closest to each other.

  5. Determining the number of clusters in a data set - Wikipedia

    en.wikipedia.org/wiki/Determining_the_number_of...

    Explained Variance. The "elbow" is indicated by the red circle. The number of clusters chosen should therefore be 4. The elbow method looks at the percentage of explained variance as a function of the number of clusters: One should choose a number of clusters so that adding another cluster does not give much better modeling of the data. More ...

  6. Today’s NYT ‘Strands’ Hints, Spangram and Answers for ...

    www.aol.com/today-nyt-strands-hints-spangram...

    Drag or tap letters to create words. If tapping, double tap the last letter to submit. Theme words fill the board entirely. No theme words overlap.

  7. Distance matrix - Wikipedia

    en.wikipedia.org/wiki/Distance_matrix

    A common function in data mining is applying cluster analysis on a given set of data to group data based on how similar or more similar they are when compared to other groups. Distance matrices became heavily dependent and utilized in cluster analysis since similarity can be measured with a distance metric. Thus, distance matrix became the ...

  8. Are Christmas trees toxic to cats? How to cat-proof your home ...

    www.aol.com/christmas-trees-toxic-cats-cat...

    Cats are known to climb on furniture and other decor, so here are some tips to cat-proof your tree this holiday season. Make sure your Christmas tree has a heavy base, Purina recommends. This will ...

  9. Best Buy broadly misses earnings estimates as consumers pull ...

    www.aol.com/finance/best-buy-expected-see...

    For the 12th consecutive quarter, Best Buy posted negative same-store sales growth. Net sales and earnings per share also missed estimates.