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The estimated logit model describes a non-linear regression of which the goal is to perform a forecast where the variable we want to predict is either 0 or 1 (binary). The model uses a logistic probability function to determine the relationship between the dependent and the independent variables. The difference in accuracy between this logit model and a linear probability model is shown in the graphs below.

This machine learning related activity is used to estimate a model for a binary variable and uses that model to make a one point ahead forecast for the binary variable.

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Ciphix - Simple Logit Model