Section 19.6.5 noted that the output of the logistic function could be interpreted as a probability p assigned by the model to the proposition that f(x)=1; the probability that f(x)=0 is therefore 1 – p. Write down the probability p as a function of x and calculate the derivative of log p with respect to each weight wi. Repeat the process for log(1-p). These calculations give a learning rule for minimizing the negative-log-likelihood loss function for a probabilistic hypothesis. Comment on any resemblance to other learning rules in the chapter.
The goal of this project is to integrate your various components into polished, professional products. Follow the instructions below to ensure a
The goal of this project is to integrate your various components into polished, professional products. Follow the instructions below to ensure a successful submission: Apply Feedback: Review and incorporate all feedback received from previous submissions (Parts 2-6). Enhance and Improve: Refine any of the three required items (cover letter with