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@article{175574,
        author = {surya ravichandran},
        title = {Analogy of H2O ranking and its stratification using SVM and XGBoost method},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {3975-3981},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175574},
        abstract = {Water is an important part of the human being and the living society. Over the number of years water has been contaminated by the various ways of the air and water pollution. This makes the content to be unhygienic and harmful for the drinking and society. The traditional method of water purification is expensive and it involves a lot of unnecessary time with the outcome of the results not up to the accuracy. My proposed system of thesis is to develop the classification of the water quality using the Gradient boosting classifier. My research involves considering of the various parameters of H2o including the pH, dissolved oxygen, Total Dissolved Solids (TDS), temperature which is predominant for the ranking of water contents.},
        keywords = {Support Vector Machine (SVM), XGBoost, Gradient Boosting Classifier, Machine Learning, Climate Models Integration.},
        month = {April},
        }