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\begin{algorithm}{SMOTE}[$T$,~$N$,~$k$] {
	\qinput{Number of minority class samples $T$; Amount of SMOTE $N$\%; Number of nearest neighbors $k$}
	\qoutput{($N/100$) * $T$\space synthetic minority class samples}} 
	\qcom{{\it{If $N$\space is less than 100\%, randomize the minority class samples as only a random percent
of them will be SMOTEd.}}} \\	\qif $N < 100$\space \\	\qthen Randomize the $T$\space minority class samples \\	$T = (N/100) * T$\space \\	$N = 100$ 
	\qfi \\	{\bf{endif}} \\	$ N = (int)(N/100) $\space \qcom{{\it{The amount of SMOTE is assumed to be in integral multiples of 100.}}} \\	$k$\space = Number of nearest neighbors \\	$numattrs$\space = Number of attributes \\	$Sample[~][~]$: array for original minority class samples \\	$newindex$: keeps a count of number of synthetic samples generated, initialized to 0 \\	$Synthetic[~][~]$: array for synthetic samples \newline
\qcom{{\it{Compute $k$\space nearest neighbors for each minority class sample only.}}}\\	\qfor $i \qlet 1$\space \qto $T$\space \\	 	Compute $k$\space nearest neighbors for $i$, and save the indices in the $nnarray$\space \\		Populate($N$, $i$, $nnarray$) \qrof  \\	{\bf{endfor}} \newline 
	
	\qproc[N,~i,~nnarray]{Populate} \qcom{{\it{Function to generate the synthetic samples.}}} \\ 
	\qwhile $N \neq 0$\space \\		Choose a random number between $1$\space and $k$, call it $nn$. This step chooses one of the $k$\space nearest 
		neighbors of $i$.  \\	\qfor $attr \qlet 1$\space \qto $numattrs$\space \\		Compute: $dif = Sample[nnarray[nn]][attr] - Sample[i][attr]$\space  \\		Compute: $gap$\space = random number between 0 and 1 \\		$Synthetic[newindex][attr] = Sample[i][attr] + gap * dif$\space \qrof \\	
	{\bf{endfor}} \\		$newindex$++ \\	$N = N - 1$\space \qelihw \\	{\bf{endwhile}} \\	\qreturn  \qcom{{\it{End of Populate.}}}\newline
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