MeanNearestNeighbors (MNN) - algorithm for balancing dataset - In progress #1

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One of the challenges in classification problems are unbalanced datasets. I was Data Science Intern when the company that I worked for, assigned me such an interesting challenge where the dataset was unbalanced.  However, I realized this type of problem like unbalanced dataset is а common thing in real life. I tried most of the algorithms (undersampling, oversampling) like SMOTE, NearMiss, CondensedNearestNeighbors, RandomUnderSampler, RandomOverSampler,  KMeansSMOTЕ and rest of them. Anyway, they didn't help me in that case, on the contrary, they worsened my model.  I was like: "but, but, you should have been helpful in creating the predictive model" So, I'm trying to create another algorithm based on undersampling concept when it comes to balancing datasets. I called it Mean Nearest Neighbors (MNN). What's the initial idea: It's simple. Actually, the algorithm is just a modification of the other undersampling algorithms. In the data where target labe...

Competitive Programming #10: [Connected graph, cycles, edges,BiParity]

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We have graph : (Its bad but is okay as example 😀😀😀)



1. Check if graph is connected at all ! (Are all nodes are connected)
2. Are there any cycles ?!
3. How many edges has in this graph?!
4. Check if graph is BiParity (No adjacent nodes are even or odd numbers)
Here is the Code:

Simply use Depth-First Search (is more better choice,cause it is easier to implement).

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