I am novice in Gurobi Language. I am trying to solve some LPs and MIPs using GurobiPy, so the approach I thought I would take was to look at some examples how to add constraints and all. But in the examples provided by Gurobi website, the actual documentation on how to add mathematical constraints to the model was like finding a needle in haystack. From my fellow seniors I would like to know how can I approach to learn to add constraints actually. Thank you. I already found some understanding, but there are things like sum( * , 1) etc which I don't really understand.
These tutorials can be a starting point:
https://www.gurobi.com/resource/abremod-getting-started-intro/
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This is a rather general question: There is this webpage which lets you calculate Eigenvalues, Eigenspaces, etc... It also gives you step-by-step solutions. Is there any coding language or module (preferably in Python) which makes it easier to code something like this, or must this be coded manually?
Thank you for your help.
i hope you all will be doing fine.
I am having a conceptual problem,I dont know the name of this table and neither i know how can i extract it using scikit-learn.Even, if i knew the correct terminology for this table that would have helped a lot or if someone can tell me, which scikit function to use then it will be awesome.
i have googled it a lot e.g using terms like aggregated table, classification reports but couldn't find this type of table.
thanks for your time!
happy coding!
You can use eli5 package in python.
ELI5 is a Python package which helps to debug machine learning classifiers and explain their predictions.
For the specific case, you can use eli5.show_weights() function for your classifier. Notice that it works for classifiers in sklearn and sklearn-crfsuit also.
Sorry for the late reply, but I discovered after searching and discussion with my peers. This is custom matrix used for algorithm comparison on the basis of feature extraction techniques. Thanks #OmG for taking your time to answer this question.
I'm currently solving a shift assignment problem in OR-tools in Python, using a MIP solver, one employee at a time. For each seperate problem there is one employee and around 100 shifts. There are a lot of variables and constraints (few 1000's per employee). I've already looked in detail on how to improve each constraint, but no luck. Since the performance is really important, I wanted to further investigate the possibilities to adjust the search strategies, but no luck either. It seems that the documentation is sparse.
Can anyone help me by giving me some options to look into?
This is the solver I'm using:
pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING
Thank you in advance. Let me know if there is any information I need to add here.
You are out of luck. There are no customisation available for the search through the linear solver wrapper.
I would suggest using the CP-SAT for this.
You can have a look at:
https://github.com/google/or-tools/blob/master/examples/python/shift_scheduling_sat.py
I am learning to use lpsolve in python to solve the linear programming, I followed the website, and it worked well. But I could not find where to set the max/min attribute in LP problem, it has tortured me for some days.
taking a quick look, it seem to me you need to use set_maxim and set_minim, as in here. from python code it would be:
lpsolve('set_maxim', lp)
or
lpsolve('set_minim', lp)
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Possible Duplicate:
Learning efficient algorithms
I recently came across an problem that was solved by applying the correct algorithm: Calculating plugin dependencies
While I was eventually able to understand the logic of the prescribed algorithm, it was not an easy task for me. The only reason I was able to come up with code that worked was because of the logic example on the wikipedia page.
Being entirely self taught, without any CS or math background, I'd like to at least get some practical foundation to being able to apply algorithms to solve problems.
That said, are there any great books / resources (something akin to 'algorithms for dummies') that doesn't expect you have completed college Algebra 9 or Calculus 5 that can teach the basics? I don't expect to ever be a wizard, just expand my problem solving tool-set a little bit.
Doing an amazon search turns up a bunch of books, but I'm hoping you guys can point me to the truly useful resources.
The only language I have any real experience with is Python (a tiny bit of C) so whatever I find needs to be language agnostic or centred around Python/C.
"Art of Computer Programming" by Donald Knuth is a Very Useful Book.
A great book is "Introduction to Algorithms" by Cormen, Leiserson, Rivest and Stein.
Probably not the easiest one but it is very good indeed.
I found useful for myself the following sources:
"Analysis of Algorithms : An Active Learning Approach" by Jeffrey J. McConnell;
"Python Algorithms: Mastering Basic Algorithms in the Python Language"(Expert's Voice in Open Source) by Magnus Lie Hetland. - this books seems to me to be a very like a previous book but from python developer point of view;
http://en.wikipedia.org/wiki/Structure_and_Interpretation_of_Computer_Programs
Steve Skiena's Algorithm Design Manual is very good. It doesn't assume very much background knowledge, and covers several important topics in algorithms.
Personally I found Algorithms and Complexity to be super helpful. I'm also without CS degree or anything.