Unsupervised Learning - Kmeans Week 11 Challenge

ans 1= For categorical data, similarity can be calculated using various metrics such as:

1. Hamming Distance: It measures the number of positions at which the corresponding symbols are different.

2. Jaccard Similarity: It calculates the size of the intersection divided by the size of the union of two sets. This is often used for comparing sets of categorical data.

3. Dice Similarity Coefficient: Similar to Jaccard, but it's another measure of set similarity that takes into account both the number of shared elements and the size of the sets.

4. Categorical Cross-Entropy: It measures the dissimilarity between two probability distributions over the categories. It is commonly used in the context of classification problems.

The choice of similarity metric depends on the nature of your categorical data and the specific requirements of your analysis.