Sadhu and Cholit bhasha are two significant Bangladeshi languages. Sadhu was functional in ancient era and had Sanskrit components but in present era cholit took its place. There are many formal and legal paper works present in Sadhu language which direly need to be translated in Cholit because it's more favorable and speaker friendly. Therefore, this paper dealt with this issue by familiarizing the current era with Sadhu by creating a software. Different sentences were chosen and final data set was obtained by Principal Component Analysis (PCA). MATLAB and Python are used for different machine learning algorithms. Most work is being done using Scikit-Learn and MATLAB machine learning toolbox. It was found that Linear Discriminant Analysis (LDA) functions best. Speed prediction was also done and values were determined through graphs. It was inferred that this categorizer efficiently translated all Sadhu words to Cholit precisely and in well-structured way. Therefore, Sadhu will not remain a complex language in this decade.
Cholit, Inverse Data Frequency, Linear Discriminant Analysis, Principal Component Analysis, Sadhu, Term Frequency, Machine Learning
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