This project deals with 2 differnt data sets one is human dataset from kaggale and anoher from physionet. 1st data set deals with dna family 2nd data set deals with +ve class dna or -ve class dna. This project carried out with the help of Nature Inspiried Algorithms and normal hyperparameter tuining. NIA is applied for 2nd data set and hyperparameter tuning applied for human dataset(1st). The csv files, coding part and a PPT attached for the reference to know hoe]w the project work flows.
NIA approach deals with adding dummie values during classification where as in hyperparameter tuning NLP(natural language process) has been used for DNA sequences before classification. The NLP steps are been clearly explained in PPT.
Deoxyribo Nucleic Acid (DNA) is a unique macromolecule of all living species. It passes on the hereditary data of life. Artificial Intelligence can be used to classify the DNA class based on the sequence, as it can reduce the time taken and can enhance the information managing limits compared to a manual technique that is followed for ages. The main objective of this project is to develop a machine learning model that can improve the classification of DNA sequences.
