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@@ -1333,7 +1333,7 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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- "# Select 5 Most Correlated Variables with Final Score"
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+ "# Select 6 Most Correlated Variables with Final Score"
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]
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},
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{
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@@ -1357,7 +1357,7 @@
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" # Find correlations with the Grade\n",
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" most_correlated = df.corr().abs()['Grade'].sort_values(ascending=False)\n",
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" \n",
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- " # Maintain the top 5 most correlation features with Grade\n",
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+ " # Maintain the top 6 most correlation features with Grade\n",
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" most_correlated = most_correlated[:8]\n",
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" \n",
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" df = df.ix[:, most_correlated.index]\n",
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@@ -3545,7 +3545,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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- "version": "3.6.4"
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+ "version": "3.6.5"
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}
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},
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"nbformat": 4,
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