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17 changes: 17 additions & 0 deletions Feature Engineering- Missing Values Day 2.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -1215,6 +1215,23 @@
"sns.boxplot('Age_end_distribution',data=df)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Advantages\n",
"1. Easy to implement\n",
"2. Captures the importance of missingess if there is one\n",
"\n",
"### Dsiadvantages\n",
"1. Distorts the original distribution of the variale\n",
"2. If missingess is not importrant, it may mask the predictive power of the original variable by distorting its distribution\n",
"3. if the number of NA is big, it will mask the true outliers in the distribution\n",
"4. if the number of NA is small, the replaced NA may be considered an outlier and pre-processed in a subsequent feature engineering\n",
"\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
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