K-Nearest Neighbors

Definition of K-Nearest Neighbors K-Nearest Neighbors (KNN) is a machine learning algorithm used to predict the output value of a target variable by finding the k nearest neighbors of a given input value. The algorithm assigns a weight to each neighbor, then uses a weighted average to predict the output value for the target variable….

Kurtosis

Definition of Kurtosis Kurtosis: A measure of the peakedness or flatness of a distribution, Kurtosis is determined by calculating the fourth moment of the distribution about its mean. Distributions with high kurtosis are more peaked than those with low kurtosis, while distributions with low kurtosis are more spread out. How is Kurtosis used? Kurtosis is…

Kolmogorov-Smirnov Statistic

Definition of Kolmogorov-Smirnov Statistic Kolmogorov-Smirnov Statistic: The Kolmogorov-Smirnov statistic is a measure of the difference between two distributions. It is used to determine whether the two distributions are statistically different from each other. How is Kolmogorov-Smirnov Statistic used? The Kolmogorov-Smirnov Statistic (K-S Test) is a nonparametric test used to compare the distributions of two samples….

K-means clustering

Definition of K-means clustering K-means clustering: K-means clustering is a data mining algorithm used to partition a set of data points into k clusters. Data is divided into clusters based on the similarities of the points within each cluster. This algorithm is often used to segment customers into different groups for marketing purposes. How is…

Kernel Regression

Definition of Kernel Regression Kernel Regression: Kernel regression is a type of nonlinear regression that uses a kernel function to calculate the weight of each input data point. This type of regression is often used for time series data, where the input points are close together in time. How is Kernel Regression used? Kernel Regression…

Kernel Density Estimation

Definition of Kernel Density Estimation Kernel Density Estimation: Kernel density estimation is a technique used to estimate the probability density function of a random variable. It is often used to smooth out noisy data or in cases where the exact distribution of the data is unknown. How is Kernel Density Estimation used? Kernel Density Estimation…

Kernel

Definition of Kernel Kernel: A kernel is a mathematical function that takes two inputs, typically vectors in a high-dimensional space, and outputs a scalar. The kernel function defines a similarity or distance between the two vectors. How is Kernel used? Kernel is the core component of a computerâ€™s operating system that acts as an interface…

Kappa Statistic

Definition of Kappa Statistic Kappa Statistic: Kappa statistic is a statistic used in machine learning and data science that measures the agreement between predicted values and observed values. Kappa statistic is calculated as the average of the absolute agreements (predicting the correct class) minus the average of the absolute disagreements (predicting the wrong class). How…