How to optimize a logistic regression in MATLAB?

How to optimize a logistic regression in MATLAB?

Octave/MATLAB’s fminunc is an optimization solver that finds the minimum of an unconstrained function. For logistic regression, you want to optimize the cost function J (θ) with parameters θ.

How to calculate Fourier transform in MATLAB spectrogram?

s = spectrogram (x,window,noverlap,nfft) uses nfft sampling points to calculate the discrete Fourier transform. [s,w,t] = spectrogram (___) returns a vector of normalized frequencies, w, and a vector of time instants, t , at which the spectrogram is computed. This syntax can include any combination of input arguments from previous syntaxes.

Which is an example of a spectrogram in MATLAB?

Example: spectrogram(x,100,’OutputTimeDimension’,’downrows’) divides x into segments of length 100 and windows each segment with a Hamming window of that length The output of the spectrogram has time dimension down the rows.

How to estimate the reassigned spectrogram of a signal?

Specify the chirp so that its frequency is initially 100 Hz and increases to 200 Hz after 1 second. Estimate the reassigned spectrogram of the signal. Divide the signal into sections of length 128, windowed with a Kaiser window with shape parameter β = 1 8. Specify 120 samples of overlap between adjoining sections.

How to build a machine learning logistic regression model?

To help make the decision, we have a dataset of test results on past microchips, from which we can build a logistic regression model. plotDecisionBoundary.m is used to generate a figure where the axes are the two exam scores, and the positive (y = 1, accepted) and negative (y = 0, rejected) examples are shown with different markers.

Which is an example of a logistic regression?

Logistic regression is a special type of regression in which the goal is to model the probability of something as a function of other variables. Consider a set of predictor vectors where is the number of observations and is a column vector containing the values of the predictors for the th observation.

Which is the best way to fit a nonlinear logistic regression?

This example shows two ways of fitting a nonlinear logistic regression model. The first method uses maximum likelihood (ML) and the second method uses generalized least squares (GLS) via the function fitnlm from Statistics and Machine Learning Toolbox™.