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what is the difference between linear regression and logistic regression?
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linear regression is a type of regression analysis which is used to predict the value of a dependent variable by fitting a linear equation to a dataset. it assumes the relationship between independent and dependent variables to be linear and the model is trained using a least-squares optimization algorithm. on the other hand, logistic regression is a type of classification technique used to predict the probability that an instance belongs to a certain class. it is used when the dependent variable is binary and the independent variables are continuous. it is trained using a logistic/sigmoid function so that the output probabilities are between 0 and 1.
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