Category «Machine Learning»

Support Vector Machine-SVM

A Support Vector Machine is a supervised algorithm that can classify cases by finding a separator. SVM works by first mapping data to a high dimensional feature space so that data points can be categorized, even when the data are not otherwise linearly separable. Then, a separator is estimated for the data. Lets X is …

Parametric vs Non Parametric Algorithm

It depends on whether the number of parameters in the model grows as the number of examples in the dataset grows. Here, parameter means the entity that measures the model like median. Parametric :Fixed number of parameters regardless of the number of examples. Liner Regression Logistic Regression Linear Discriminant Analysis Perceptron Naive Bayes Non-Parametric: Not …

Generalized Linear Models

Here general refers to the dependence on potentially more than one explanatory variable, v.s. the simple linear model : Some of the Generalized liner models are: 1-Ordinary Least Squares :Linear Regression fits a linear model with coefficients to minimize the residual sum of squares between the observed responses in the data set, and the responses …

learning Model

https://machinelearningmastery.com/5-step-life-cycle-neural-network-models-keras/