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I was learning for my Exams and I think im missing out on Something about the Traveling Salesman Problem, maybe some of you Guys can help me out
I was wondering If you couldn't use a MST to first find all the Vertices and afterwards use A* to get back to the starting point ? would that be polynomial complexity or am I missing out on Something.
edit: or use any other point-to-point shortest path algorithm
I appreciate any help or answers
The MST doesn't give you a single path containing all the vertices. Also the TSP asks you to find the shortest path, not just any path.
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For a course term project we have to build a machine learning algorithm in which user fills the form and the algorithm analyse the best suitable university based on the responses. I am new in the field of machine learning and I do not know what kind of algorithm can we use. Is the recommendation systems a right approach for this?
I did some review on the internet for some similar projects, however still can not find a good resource.
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I am looking for the machine learning correct approach for predicting the lottery numbers, not the most accurate answer but at least we have some predicted output. I am implementing the regression based and neural network models for this. Is their any specific approach which follows this?
It is impossible. The lottery numbers are random - actually to be more specific, the system is chaotic. You would require the initial configuration (positions etc) to insane (possibly infinite) precision to be able to make any predictions. Basically, don't even try it.
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Could someone kindly explain to me in layman terms, or refer me to any articles, why when doing machine learning (e.g. classification model) sometimes we need to turn continuous numeric feature into nominal?
Also, are there times where doing so is not a good idea...e.g. can cause overfitting...or?
Thanks
Wes
This article has a nice explanation
8 Ways to deal with Continuous Variables in Predictive Modeling
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I wrote a ruby script that finds a solution to the Bays29 travelling salesman problem. The bays29 data set is found here:
http://elib.zib.de/pub/mp-testdata/tsp/tsplib/tsp/bays29.tsp
Now say my solution is in an array that says go to city 1, then 4, then 9 etc..
I want to show this visually being solved somehow. For e.g. I would like to have it in a browser showing all the cities connected together and then the solution gets highlighted after it is generated.
How can I go about doing this?
What kind of gems should I use?
Thanks a lot!
You could write a small Rails app with the algorithm in a model and some javascript (with either OpenLayers or Leaflet) for map visualization.
The traveling salesman is a hard problem, so it might take a while to calculate a result. You could use AJAX or Server Side Events to update the map when the server has found a better soluton.
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I would like to interpret problem on picture below, which is about perceptron learning. It is about supervised learning wiht a training set, so correctness of values should be checked against a predefined set of values. I don't exactly know, how A, B and bias(b) values come. Could you please explain meaning of these and how these computed and changed during the learning process?
Here you have an intuitive, visual, interactive and beautiful guide to the basics concepts of neural networks:
https://jalammar.github.io/visual-interactive-guide-basics-neural-networks/
It will problably solve all your doubts. However, if you still have more questions after the reading, you will be able to ask something more specific. Enjoy!