Logistic Regression turns a weighted input score into a probability. ModelOrigen exposes the exact path from a selected sample to z, sigmoid(z), the class decision, loss, gradient, and the next recorded parameter state.
Open the interactive visualizer →The model computes a weighted sum, maps it through the sigmoid function, compares the probability with the target, and updates weights and bias from the calculated gradient.
The main visualizer runs the implemented model in your browser and exposes the stored state, predictions, and metrics instead of substituting fabricated demo numbers.
Start with the default educational dataset, predict what will happen, run the model, then inspect one calculation or parameter at a time. For supported CSV workflows, local files are parsed and processed in the browser rather than uploaded by the application.