https://github.com/mehrab-kalantari/book-price-prediction

Book price dataset analysis and modeling
https://github.com/mehrab-kalantari/book-price-prediction

bivariate-analysis eda feature-engineering feature-extraction feature-importance nlp one-hot-encoding ordinal-encoding outlier-detection random-forest-regressor scaling univariate-analysis

Last synced: 3 months ago
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Book price dataset analysis and modeling

• Host: GitHub
• URL: https://github.com/mehrab-kalantari/book-price-prediction
• Owner: Mehrab-Kalantari
• Created: 2023-12-05T07:56:04.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-12-05T08:09:41.000Z (over 1 year ago)
• Last Synced: 2025-01-16T09:42:47.034Z (5 months ago)
• Topics: bivariate-analysis, eda, feature-engineering, feature-extraction, feature-importance, nlp, one-hot-encoding, ordinal-encoding, outlier-detection, random-forest-regressor, scaling, univariate-analysis
• Language: Jupyter Notebook
• Homepage:
• Size: 1.71 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Book Prices Prediction

## Contents

### Data Understanding

Understanding data and features

![info](sample/info.png)

### Data Cleaning For EDA

* Renaming columns

* Categorical to numerical 

* Feature expansion

* Feature extraction

* Null values handling

### Exploratory Data Analysis

* Univariate Analysis

  * Target analysis

  * Numerical features

  * Categorical features

* Bivariate Analysis

  * Year analysis

  * Population analysis

  * Price analysis

### Data Preprocessing

* Target Log

* Encoding

    * Ordinal

    * One Hot

    * Count Vectorizer

* Discretization

* Normalization

* Scaling

* Standardization

* Outlier Detection

### Modeling

Random forest regressor is used.

### Evaluation

MSE for train and test datasets

* Train MSE

* ![tr](sample/train.png)

* Test MSE

* ![te](sample/test.png)

### Feature Importance

![f](sample/feat.png)