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sanjay-kv
Karansankhe
Overview This pull request introduces the Genetic Disorder prediction project to the repository. The project folder includes the following files:
1)Gd.ipynb: This file contains: Implementation of various machine learning models for predicting Genetic Disorders. Visualizations depicting data insights and relationships among variables.
2)Readme.md: Provides setup instructions and a basic overview of the project. Includes details on how to install dependencies and run the project.
3)train.csv and test.csv: These CSV files contain data used for training and testing the machine learning models. Purpose The project aims to predict Genetic Disorders using machine learning techniques. It involves data preprocessing, exploratory data analysis through visualizations, model evaluation, and prediction.
Implemented machine learning models: Gaussian Naive Bayes, Support Vector Classifier (SVC), Random Forest, Logistic Regression, and K-Nearest Neighbors. Conducted cross-validation to assess model performance. Created visualizations to gain insights into data distribution and relationships.