Category: Machine Learning
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K-means Clustering Algorithm
Table of Contents Definition K-means clustering is an unsupervised machine learning method used to partition a set of observations into k clusters. Unsupervised learning in artificial intelligence is a type of machine learning that learns from data without human supervision. Unlike supervised learning, unsupervised machine learning models are given unlabeled data and allowed to discover patterns and insights…
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Naive Bayes Classifier
Table of Contents Definition Naive Bayes classifier is a family of linear “probabilistic classifiers” which assumes that the features are conditionally independent, given the target class. The strength (naivety) of this assumption is what gives the classifier its name. These classifiers are among the simplest Bayesian network models. Naive Bayes classifiers are highly scalable, requiring a…
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K-Nearest Neighbors(KNN) Algorithm
Table of Contents Definition KNN(K-nearest neighbors algorithm is a non-parametric supervised learning for classification and regression. Types of KNN(K-nearest neighbors) Formulation Feature of KNN KNN Steps Decision Boundary Voronoi Diagram With large number of examples and possible noise in the labels, the decision boundary can become nasty. Effect of K Larger k produces smoother boundary…
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Random Forest Algorithm
Table of Contents Definition Random forests or random decision forests is an ensemble learning method for classification, regression and other tasks that operates by constructing a multitude of decision trees at training time. For classification tasks, the output of the random forest is the class selected by most trees. For regression tasks, the mean or average prediction of the individual trees is returned.…
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SVM(Support Vector Machine)
Table of Contents Definition In machine learning, support vector machines (SVMs, also support vector networks) are supervised max-margin models with associated learning algorithms that analyze data for classification and regression analysis. A support vector is a data point or node lying closest to the decision boundary or hyperplane. These points play a vital role in defining the decision boundary and the margin of…
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Decision Tree
Table of Contents Definition A decision tree is a decision support hierarchical model that uses a tree-like model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains conditional control statements. A decision tree is a flowchart-like structure in which each internal…
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Logistic Regression
Table of Contents Definition In statistics, the logistic model (or logit model) is a statistical model that models the log-odds of an event as a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) is estimating the parameters of a logistic model (the coefficients in the linear combination). Formally, in…
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Linear Regression
Table of Contents Definition In statistics, linear regression is a statistical model which estimates the linear relationship between a scalar response(known as dependent variable or target variable) and one or more explanatory variables (known as independent variables or predictor variables). Linear regression is an analytics procedure that can generate predictions by using an easily interpreted mathematical formula.…
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