When I was learning this part, I found it very confusing too, so I put together the two pseudo-codes from R.Sutton and A.G.Barto hoping to make the difference clearer. Blue boxes highlight the part where the two algorithms actually differ. Numbers highlight the more detailed difference to be explained later. TL;NR: | | SARSA | … Read more
I think there is a lot of confusion about which weights are used for what. I am not sure I know precisely what bothers you so I am going to cover different topics, bear with me ;). Class weights The weights from the class_weight parameter are used to train the classifier. They are not used … Read more
From wikipedia: A genetic algorithm (GA) is a search technique used in computing to find exact or approximate solutions to optimization and search problems. and: Neural networks are non-linear statistical data modeling tools. They can be used to model complex relationships between inputs and outputs or to find patterns in data. If you have a … Read more
Dijkstra is a special case for A* (when the heuristics is zero).
The training and validation sets are used during training. for each epoch for each training data instance propagate error through the network adjust the weights calculate the accuracy over training data for each validation data instance calculate the accuracy over the validation data if the threshold validation accuracy is met exit training else continue training … Read more
Lisp WAS used in AI until the end of the 1980s. In the 80s, though, Common Lisp was oversold to the business world as the “AI language”; the backlash forced most AI programmers to C++ for a few years. These days, prototypes usually are written in a younger dynamic language (Perl, Python, Ruby, etc) and … Read more
Not homework. My first job as a professional programmer (1995) was writing a genetic-algorithm based automated trading system for S&P500 futures. The application was written in Visual Basic 3 [!] and I have no idea how I did anything back then, since VB3 didn’t even have classes. The application started with a population of randomly-generated … Read more
Let me add my 2ยข, it’s my job to get good and clean data for a hedge-fund, I’ve seen quite a lot of data feeds and historical data providers. This is mainly about US stock data. To start with, if you have some money don’t bother with downloading data from Yahoo, get the end of … Read more
Since you ask this very basic question, it looks like it’s worth specifying what Machine Learning itself is. Machine Learning is a class of algorithms which is data-driven, i.e. unlike “normal” algorithms it is the data that “tells” what the “good answer” is. Example: a hypothetical non-machine learning algorithm for face detection in images would … Read more
I second the motion to do a lot more games per match. Doing 50 games is just flipping a coin. I needed to do 1000 games to get any reasonable distinction between test algorithms. Download Dreadnought 1.2. Strategies: keep track of all possible positions for ships that have >0 hits. The list never gets bigger … Read more