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Tag Archives: R Machine-Learning

A regression line is basically used in statistical models which help to estimate the relationship between a dependent variable and at least one independent variable.… Read More
Linear regression is a method of predictive analysis in machine learning. It is basically used to check two things: If a set of predictor variables… Read More
Machine Learning is a subset of artificial intelligence that focuses on the development of computer software or programs that access data to learn themselves and… Read More
Cluster analysis or clustering is a technique to find subgroups of data points within a data set. The data points belonging to the same subgroup… Read More
Feature engineering is the most important technique used in creating machine learning models. Feature Engineering is a basic term used to cover many operations that… Read More
Prerequisite: Multiple Linear Regression using R A well-fitting regression model produces predicted values close to the observed data values. The mean model, which uses the… Read More
Arthur Samuel, a pioneer in the field of artificial intelligence and computer gaming, coined the term “Machine Learning”. He defined machine learning as – “Field… Read More
Apriori algorithm is used for finding frequent itemsets in a dataset for association rule mining. It is called Apriori because it uses prior knowledge of… Read More
Packages in the R programming are a collection of R functions, compiled code, and sample data. They are stored under a directory called “library” in… Read More
A popular nonparametric(distribution-free) test to compare outcomes between two independent groups is the Mann Whitney U test. When comparing two independent samples, when the outcome… Read More
The prime aim of any machine learning model is to predict the outcome of real-time data. To check whether the developed model is efficient enough… Read More
Repeated K-fold is the most preferred cross-validation technique for both classification and regression machine learning models. Shuffling and random sampling of the data set multiple… Read More
LOOCV(Leave One Out Cross-Validation) is a type of cross-validation approach in which each observation is considered as the validation set and the rest (N-1) observations… Read More
The validation set approach is a cross-validation technique in Machine learning. Cross-validation techniques are often used to judge the performance and accuracy of a machine… Read More
Quantile Regression is an algorithm that studies the impact of independent variables on different quantiles of the dependent variable distribution. Quantile Regression provides a complete… Read More