Update README.md

README.md

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 `calzone` is a comprehensive Python package for calculating and visualizing various metrics for assessing the calibration of models with probabilistic output. 
 
-To accurately assess the calibration of machine learning models, it is essential to have a comprehensive and reprensative dataset with sufficient coverage of the prediction space. The calibration metrics is not meaningful if the dataset is not representative of true intended population.
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 ## Features
 
 - Supports multiple calibration metrics including Spiegelhalter's Z-test, Expected Calibration Error (ECE), Maximum Calibration Error (MCE), Hosmer-Lemeshow test, Cox regression analysis, and Loess regression analysis
@@ -16,6 +13,8 @@ To accurately assess the calibration of machine learning models, it is essential
 - Prevelance adjustment to account for prevalance change between enriched data and population data.
 - Multiclass extension by 1-vs-rest or top-class only
 
+To accurately assess the calibration of machine learning models, it is essential to have a comprehensive and reprensative dataset with sufficient coverage of the prediction space. The calibration metrics is not meaningful if the dataset is not representative of true intended population.
+
 ## Installation
 
 You can install calzone using pip: