can you use the least squares method for logistic regression
No, the least squares method cannot be directly used for logistic regression. The least squares method is used for linear regression, where the goal is to minimize the sum of squared residuals between the observed and predicted values.
In logistic regression, the response variable is binary (i.e., categorical with two levels) and the predicted values are probabilities between 0 and 1. Logistic regression uses a different approach called maximum likelihood estimation to estimate the parameters of the model. The goal is to maximize the likelihood of observing the given data, given the estimated parameters.
Therefore, logistic regression requires a different method, such as maximum likelihood estimation or gradient descent, to estimate the parameters of the model.