A one-way plot, which is generated by the JMP Fit Y by X platform, shows the response points along the y-axis for each X factor value. Using the plot, you can compare the distribution of the response across the levels of the X factor. The distinct values of X are sometimes called levels.
The one-way plot below shows the relative success of several predictive models at predicting the response in a set of data after cross validation. In this case, each model corresponds to one X factor level and the average root mean square error (RMSE) represents the response for that model.
This plot shows the RMSE for each model across each cross validation run. For the random cross validation method used in this example, the plotted RMSE represents the average of the RMSE for each of the runs for a particular predictive modeling method. The smaller the RMSE is, the better the model is at predicting the response. Note the black, horizontal line at RMSE 0.5. This line represents the average RMSE if there is no predictive model. Any model whose RMSE approaches or exceeds this value is to be considered unreliable. Radial Basis Machine (M8_RBM_Nicardipine_ARM), showing the smallest average RMSE, appears to be the best model for this data, although the comparison circles indicate that it is not significantly different from several other models.