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Title
Enhancement of Smartphone Price Prediction Model Using Dataset
Enhancement Aim
The aim of this enhancement is to improve the accuracy and performance of the existing machine learning model that predicts smartphone prices based on features such as ratings and the number of reviews. This includes refining data preprocessing, experimenting with different machine learning algorithms, and enhancing visualization for better insights.
Changes
Data Preprocessing: Implement additional data cleaning steps to handle missing values and outliers more effectively. Feature Engineering: Explore additional features from the dataset (e.g., brand, specific model details) to enhance the predictive capability of the model. Model Comparison: Compare different regression models (e.g., Linear Regression, Random Forest, XGBoost) and select the best performing model. Performance Evaluation: Add additional performance metrics (e.g., MAE, R²) to better assess model accuracy. Visualization Enhancements: Create more comprehensive visualizations, such as distribution plots for predicted prices and feature importance plots.
Screenshots 📷
N/A
Guidelines
Full Name
Benak Deepak
Participant Role
GSSOC