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@article{169530,
        author = {Shreerup M Manchalwar and Prem Deepak Varma and Aniket V. Meshram and Prof. N. H. Deshpande},
        title = {Startup Profitability Prediction using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {1157-1159},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169530},
        abstract = {This paper presents the ML-Based Startup Profit Predictor, an innovative tool designed to support decision-making in the startup ecosystem. Using information from a large dataset of investor profiles and business specifics, this application uses machine learning to predict a firm's profitability. It helps investors manage portfolios while lowering risks and helps entrepreneurs hone their strategy by offering data-driven insights. The ultimate objective is to develop a machine learning model that can accurately forecast business performance, which is a difficult task because look-ahead bias can skew findings. In contrast to earlier attempts, this study aimed for a realistic model with useful, actionable outcomes by avoiding the use of knowledge that would not have been known at the time of decision-making.},
        keywords = {Support vector Machine (SVM), Random Forest (RF), Profit Prediction, Machine Learning, Startups, Data, Entrepreneurs, Investors, Findings, Dataset, Predictor, Profitability},
        month = {November},
        }