What is Regression analysis : Regression analysis is a statistical technique used to examine the relationship between two or more variables. It is often used to predict the value of one variable (the dependent variable) based on the value of another variable (the independent variable). For example, consider a company that wants to understand the […]

Regression : Regression is a statistical technique that is used to predict a continuous outcome based on one or more predictor variables. It is a widely used tool in many fields, including economics, finance, and marketing, to name a few. To understand regression, it is helpful to start with an example. Suppose you are a […]

Recall : Recall is a metric used to evaluate the performance of a machine learning model, specifically in classification tasks. It is defined as the number of true positive predictions made by the model, divided by the total number of positive instances in the test set. In other words, it measures the proportion of actual […]

Random walk : A random walk is a mathematical concept that describes the movement of an object or a series of events as a sequence of random steps. It is often used to model the behavior of financial markets, where prices tend to move randomly over time, influenced by various factors such as economic conditions, […]

Random variable : A random variable is a variable that takes on different values depending on the outcome of a random event. In other words, it is a variable whose value is determined by chance. There are two main types of random variables: discrete and continuous. Discrete Random Variable : A discrete random variable is […]

Random Forest : Random Forest is a machine learning algorithm that belongs to the ensemble learning method. It is used for classification and regression problems. It creates a forest of decision trees, where each tree is trained on a different set of data and makes a prediction. The final prediction is made by taking the […]

R : R is a programming language and software environment for statistical computing and graphics. It was developed in the early 1990s by statisticians at the University of Auckland in New Zealand and is now widely used in academia and industry for data analysis and visualization. One of the main strengths of R is its […]