<p>I know I'm a little too late to answer your question but hope this answer would help others! The package you're using is <code>DMwR</code> which uses a  <a href="https://arxiv.org/pdf/1106.1813.pdf" rel="nofollow noreferrer">combination of SMOTE and under-sampling of the majority class</a>.</p>

<p>I'd suggest you to use <code>smotefamily::SMOTE</code> as it only over samples the minority class, so you wouldn't lose your majority class observations.</p>
SMOTE in r reducing sample size significantly
<p>I have a data set with around 130000 records. The records divided in two class of target variable,0 &amp; 1. 1 contains only 0.09% of total proportion.</p>

<p>I'm running my analysis in R-3.5.1 on Windows 10. I used SMOTE algorithm to work with this imbalanced data set.</p>

<p>I used following code to handle imbalanced data set</p>

<pre><code>library(DMwR)
data_code$target=as.factor(data_code$target) #Converted to factor as 
# SMOTE works with factor data type
smoted_data &lt;- SMOTE(target~., data_code, perc.over=100)
</code></pre>

<p>But after executing the code,I'm seeing the count for 0 is 212 &amp; 1 is also 212 which is significant reduction of my sample size.Can you suggest me how do I handle this imbalanced data set with SMOTE without changing my data size</p>