Update and rename README.md to README.Rmd

README.md → README.Rmd

@@ -17,6 +17,6 @@ The primary objective of this thesis is to develop a R package that provides eas
 
 Numerous studies on unsupervised learning algorithms for discovering prospective pheno- and endotypes have been conducted, but the existence of subgroups of asthma patients who do not respond well to conventional therapy indicates that certain phenotypes have not been effectively recognized and described.
 
-The R package aims to offer researchers with fast tools for clustering patient time series data and confirming the distinction using additional metrics such as population parameter enrichment analysis, stability after random data removal, and conventional clus- ter stability measures.
+The R package aims to offer researchers with fast tools for clustering patient time series data and confirming the distinction using additional metrics such as population parameter enrichment analysis, stability after random data removal, and conventional cluster stability measures.
 
 It is also considerable to apply these data scientific techniques to other model development areas where a distinction in heterogeneous groups due to time series data fluctuations is desired.