multiple linear regressiona linear regression algorithm is called multiple linear regression if it is having more than one independent variable linear regression is mainly used to estimate the real values based on continuous variable(sfor examplethe total sale of shop in daybased on real valuescan be estimated by linear regression logistic regression it is classification algorithm and also known as logit regression mainly logistic regression is classification algorithm that is used to estimate the discrete values like or true or falseyes or no based on given set of independent variable basicallyit predicts the probability hence its output lies in between and decision tree decision tree is supervised learning algorithm that is mostly used for classification problems basically it is classifier expressed as recursive partition based on the independent variables decision tree has nodes which form the rooted tree rooted tree is directed tree with node called "rootroot does not have any incoming edges and all the other nodes have one incoming edge these nodes are called leaves or decision nodes for exampleconsider the following decision tree to see whether person is fit or not age< yrs ye no eat lots of fast food ye unfit no fit exercise in the morning daily ye fit no unfit support vector machine (svmit is used for both classification and regression problems but mainly it is used for classification problems the main concept of svm is to plot each data item as point in ndimensional space with the value of each feature being the value of particular coordinate here would be the features we would have following is simple graphical representation to understand the concept of svm