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...

Puzzles #1: [Crack The Code]

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Maybe you have heard about this puzzle and solved but this is for who doesn't solve and doesn't understand how to solve .
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 We read all conditions .... We have 7 3 8  block 4 that says 'Nothing is correct' so 
In Block 1 - 6 8 2 we know that 8 is not correct
And in Block 5 - 7 8 0 We know that 7 and 8 aren't correct so we have only 0 as correct but wrong place.
So in Block 3 and Block 5 - 0 is on wrong place ... and It must be on first place 0 _ _
So if you think that 6 is part of 3 digit key .. you are wrong why ?
In Block 6 8 2 that says one number is correct and well placed.. Yeah right .. 6 isn't cause we already have first number and we have only 2 . 0_2
Look at Block 2 ... 6 1 4 That says One number is correct but wrong place... We need middle place ... 1 is not wrong place... 6 we said that isn't correct so we have left 4.
Finally our code is 042

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