student development program: machine learning - logistic regression project

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student development program: machine learning- logistic regression project first name last name1 1 post graduate department of environmental science, a. n. college, patna, patliputra university, bihar, india. e-mail: sushantorama@gmail.com abstract: the abstract should highlight the problem statement, the methods used in data collection and analysis, results, and recommendations. it should not exceed more than 100 words. keywords: keyword1; keyword2; keyword3; keyword4; keyword5 1. introduction briefly explain the problem statement. 2. methodology 2.1. methodological framework 2.2. data collection & storage 2.3. python libraries required for data analysis and model development scikit-learn (pedregosa et al. 2011). 2.4. data preprocessing 2.5. descriptive analysis 2.6. selection of machine learning algorithm 2.7. machine learning model development 2.7.1. feature selection 2.7.2. feature engineering 2.7.3. imbalanced data treatment 2.7.4. train-test-validation data split 2.7.5. model training 2.8. machine learning model validation 2.8.1. accuracy 2.8.2. true positive 2.8.3. false positive 2.8.4. true negative 2.8.5. false negative 2.8.6. confusion matrix …

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student development program: machine learning- logistic regression project first name last name1 1 post graduate department of environmental science, a. n. college, patna, patliputra university, bihar, india. e-mail: sushantorama@gmail.com abstract: the abstract should highlight the problem statement, the methods used in data collection and analysis, results, and recommendations. it should not exceed more than 100 words. keywords: keyword1; keyword2; keyword3; keyword4; keyword5 1. introduction briefly explain the problem statement. 2. methodology 2.1. methodological framework 2.2. data collection & storage 2.3. python libraries required for data analysis and model development scikit-learn (pedregosa et al. 2011). 2.4. data preprocessing 2.5. descriptive analysis 2.6. selection of machine ...

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