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Linear regression uses the relationship between the data points to draw a straight line. This line can be used to predict future values.

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Logistic Regression is also called logit regression. It is used to estimate discrete values {usually binary values like 0/1} from a set of independent variables.

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Polynomial Regression is a form of Linear regression known as a special case of Multiple linear regression which estimates the relationship as an nth degree polynomial.

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It is a supervised learning algorithm that is used for classifying problems. It can work well in classifying both categorical and continuous dependent variables.

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SVM algorithm is a method of classification algorithm. It is a type of supervised machine learning algorithm that provides analysis of data for classification and regression analysis.

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Grid searching is a method to find the best possible combination of hyper-parameters at which the model achieves the highest accuracy.

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A collective of decision trees is called a Random Forest. It is an improvement of the decision tree algorithm. The majority votes from the trees and predicts the final output.

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A Naive Bayes classifier assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature.

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KNN is a simple, supervised ML algorithm that can be used for classification or regression tasks - and is also frequently used in missing value imputation.

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IKNN stores all available cases and classifies any new cases by taking a majority vote of its k neighbors.

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