Do we have anything like accuracy and loss in RNN models?

I have a paper about trading which has been implemented with RNN on Tensorflow. We have about 2 years of data from trading. Here are some samples : Date,Open,High,Low,Last,Close,Total Trade Quantity,Turnover (Lacs) 2004-08-25,1198.7,1198.7,979.0,985.0,987.95,17116372.0,172587.61 2004-08-26,992.0,997.0,975.3,976.85,979.0,5055400.0,49828.65 I need to predict the the future of trading (for example, the latest 10 days ). So, how can I make…

Why is the effective branching factor used for measuring performance of a heuristic function?

For search algorithms with heuristic functions, performance of heuristic functions are measured by effective branching factor ${b^*}$ which involves total nodes expanded ${N}$ and depth of the solution ${d}$. I’m not able to find out how different values of ${d}$ affect the performance keeping same ${N}$. Put another way, why not use just the ${N}$…

How does maximum approximation of the posterior choose a distribution?

I was learning about the maximum a posteriori probability (MAP) estimation for machine learning and I found a nice short video that essentially explained it as finding a distribution and tweaking the parameters to fit the observed data in a way that makes the observations most likely (makes sense). However, in mathematical terms, how does…