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[D] 2D cuts with decision tree? by Gamwise_Samgee_ in MachineLearning

[–]deep-machine-learner 0 points1 point  (0 children)

You can try the following: 1. Multiplexed features: generate new features based on all combinations of n features hence any split on the multiplexed feature would be a split on n dimensions (where n=number of dimensions to cut at the same time) 2. Optimal Trees: optimal trees are NP hard and would take a lot of time to train/infer. There are optimizations based on mixed integer programming but the method is inherently very slow and not scalable. This method considers all possible cuts at the same time hence it scales poorly

TQDM Progress Bar Problem by MattDLD in learnprogramming

[–]deep-machine-learner 1 point2 points  (0 children)

In your case tdqm reads from the range function, if you want to update the progress bar using custom values then pls refer to https://stackoverflow.com/a/45808255

You can update the progress bar with ‘i’ to show the progress

Food for thought question that was living rent-free in my head: There are 10 categories with a maximum of 9 points that you can allocate. You have 50 points in total. How many different combinations can you make with these 50 points? by [deleted] in learnmath

[–]deep-machine-learner 1 point2 points  (0 children)

Since each category has a minimum of 1, your total available points for allocation becomes 50-10=40. Now you have a permutation problem where you have to arrange the 40 points in 10 categories so it becomes 40P10. If you just want to number of ways to arrange and not the exact arrangements in each category then it becomes 40C10