Correlation Coefficient
Correlation measures the strength and direction of the linear relationship between two variables. The formula for the correlation coefficient (Pearson’s r) is: Where:
Category: Statistics
What is Silhouette Coefficient
he silhouette coefficient is a measure of how well-separated clusters are in a clustering analysis. It provides a way to assess the quality of clustering by evaluating both the cohesion within clusters and the separation between clusters. The silhouette coefficient ranges from -1 to 1, with higher values indicating better-defined clusters. Here’s how the silhouette…
What is Mahalanobis Distance
he Mahalanobis distance is a measure of the distance between a point and a distribution, taking into account the correlation between variables. It is often used in statistics and machine learning to identify outliers and to assess the dissimilarity between a data point and a distribution. The Mahalanobis distance is defined for a point (x)…
What is Jaccard Distance
accard distance is a measure of dissimilarity between two sets. It is calculated as the complement of the Jaccard similarity coefficient and is particularly useful when dealing with binary data or sets. The Jaccard similarity coefficient measures the proportion of shared elements between two sets, and the Jaccard distance is essentially the complement of this…
What is Uniform Distribution?
uniform distribution is a probability distribution in which all outcomes or events are equally likely to occur. In other words, every possible outcome has the same probability of occurring. In Python, you can use the numpy library to generate random numbers following a uniform distribution. For example:
What is Binomial Distribution?
he binomial distribution is a discrete probability distribution that describes the number of successes in a fixed number of independent Bernoulli trials, each with the same probability of success. In other words, it models the number of successes (e.g., heads in a series of coin flips) in a fixed number of independent experiments, where each…