**Re: Logistic Regression predicted probability is either 1 or 0 (or literally 2.2204E-**
Can you post your full output?

Thanks for helping

I used the Matlab function "fitglm" to implement the logistic regression by setting the 'Distribution' parameter equals to 'binomial' :

Logi_COE_P = fitglm(training_data_matrix, result_data_matrix, 'linear', 'CategoricalVars', CategorialVariables, 'Distribution', 'binomial', 'Link', 'logit', 'BinomialSize', 1, 'DispersionFlag', true, 'Weights', OverllDataWeight);

During the training process, it gives the warnings:

Warning: Removing terms where categorical variables

appear in powers higher than linear.

> In FormulaProcessor>FormulaProcessor.removeCategoricalPowers at 510

In TermsRegression>TermsRegression.removeCategoricalPowers at 396

In GeneralizedLinearModel>GeneralizedLinearModel.fit at 1244

In fitglm at 133

In Forecast at 248

Warning: Iteration limit reached.

> In glmfit at 368

In GeneralizedLinearModel>GeneralizedLinearModel.fitter at 919

In FitObject>FitObject.doFit at 220

In GeneralizedLinearModel>GeneralizedLinearModel.fit at 1245

In fitglm at 133

In Forecast at 248

Warning: Regression design matrix is rank deficient

to within machine precision.

> In TermsRegression>TermsRegression.checkDesignRank at 98

In GeneralizedLinearModel>GeneralizedLinearModel.fit at 1262

In fitglm at 133

In Forecast at 248

For the predictions given by the trained model, it gives:

Probability of employee staying more than 3 years: 1 1 1 1 1 1 2.22E-16 2.22E-16 2.22E-16 2.22E-16 2.22E-16 2.22E-16 2.22E-16 2.22E-16

Employee number: 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Any idea what all these mean?