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 #25: [Check if a number is divisible by 8]

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Given a number n, check if it is divisible by 8.
Input:
The first line of the input contains an integer T denoting the number of test cases. For each test case, there is an integer n whose divisibility we need to check. 
Output:
For each test case, the output is 1 if the number is divisible by 8 else -1.
Constraints:
1<=T<=100
1<=digits in n<1000 span="">
Example:
Input:
2
16
15
Output:
1
-1 
--------------------------------------------------------------
Solution:
It easy, use divisibility rule for 8. The last three digits of number >=3 must be divisible by 8 ...

For more rules divisibility :
https://en.wikipedia.org/wiki/Divisibility_rule

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