this means that we can now fit linear combinations of our features (okwe have only one feature and constantbut that will change soonto the values let' consider the linear equation in getting started with python machine learning shown as followsthis can be replaced with the following equation (by replacing with )we can solve the equation for as shown in the following formulawe simply have to find the right coefficients such that the formula will give the lowest errors for all our pairs (xipiin the datasetwhich will be detected by scikit-learn after fitting the data to the class labelsthe formula will give the probability for every new data pointxthat belongs to class refer to the following codefrom sklearn linear_model import logisticregression clf logisticregression(print(clflogisticregression( = class_weight=nonedual=falsefit_ intercept=trueintercept_scaling= penalty= tol=