Closed vivekvardhan2810 closed 6 months ago
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Closing as not checked the repo and proposed same project with different name.
Why did you Close this Issue Sir As i am already working this issue @SrijanShovit, may i know the reason
Is your feature request related to a problem? Please describe.
The Feature Has the potential to improve prenatal diagnosis of birth defects and outcomes in assisted reproductive technology too.
Describe the solution you'd like
I would like to develop a machine learning-based classification system for Perinatal health Risk Predictors.
Dataset Link : https://archive.ics.uci.edu/dataset/863/maternal+health+risk
Model : Train and compare various ML models, including Decision Tree, KNN, SVC, Random Forest, Logistic Regression, Bagging Classifier, AdaBoost Classifier, and Naive Bayes.
Data Preprocessing: This activity includes the following steps.
● Handling missing values ● Handling categorical data ● Handling outliers ● Scaling Techniques ● Splitting dataset into training and test set
Evaluation: Use GridSearchCV for hyperparameter tuning and evaluate model performance using confusion matrix and classification report, Choose the best-performing model based on accuracy and other performance metrics, typically Random Forest in this case.
Describe alternatives you've considered
No response.
Additional context
No response.
Code of Conduct