dlcfg coder.DeepLearningConfig ( 'mkldnn' ) cfg.DeepLearningConfig dlcfg Call codegen (MATLAB Coder) to generate C++ code for the HelperSpeechCommandRecognition function. Attach the configuration object to the code generation configuration object. n2 x2 These are the dashed curves created by Matlab polytool function. Create a configuration object for deep learning code generation with the MKL-DNN library. When you are done, press the Close button. For example, F -statistic in the output of Matlab function regress comes. To change from least squares to a robust fitting method, use the Method menu. The shape of the pointer changes from an arrow to a cross hair when you are over the vertical line to indicate that the line can be dragged. To change the type of confidence intervals, use the Bounds menu. polytool fits by least-squares using the regression model Evaluate the function by typing a value in the x-axis edit box or by dragging the vertical reference line on the plot. To change the degree of the polynomial, choose from the pop-up menu at the top of the figure. The argument n controls the degree of the polynomial fit.
MATLAB POLYTOOL REGRESS UPDATE
The predicted value of y will update as you drag the reference line.
Polytool fits by least-squares using the regression modelĮvaluate the function by typing a value in the x-axis edit box or by dragging the vertical reference line on the plot. Plots 100(1-alpha) % confidence intervals on the predicted values. Text with current predicted value of y and its uncertainty appears to the left of the y-axis. The plot shows the fitted curve and 95% global confidence intervals on a new predicted value for the curve. This plot is graphic user interface for exploring the effects of changing the polynomial degree of the fit. Interactive plot for prediction of fitted polynomialsįits a line to the column vectors x and y and displays an interactive plot of the result.
Polytool (Statistics Toolbox) Statistics Toolbox
0 kommentar(er)
