https://github.com/hariprasath-v/av-job-a-thon-november-2022

Build a machine learning/deep learning approach to forecast the total energy demand on an hourly basis for the next 3 years based on past trends.
https://github.com/hariprasath-v/av-job-a-thon-november-2022

exploratory-data-analysis kaggle lightgbm-regressor matplotlib numpy pandas python rmse-score seaborn sklearn statsmodels timeseries-forecasting

Last synced: 4 months ago
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Build a machine learning/deep learning approach to forecast the total energy demand on an hourly basis for the next 3 years based on past trends.

• Host: GitHub
• URL: https://github.com/hariprasath-v/av-job-a-thon-november-2022
• Owner: hariprasath-v
• License: apache-2.0
• Created: 2022-11-22T06:48:12.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-07-04T07:29:09.000Z (almost 2 years ago)
• Last Synced: 2025-01-13T01:45:01.605Z (5 months ago)
• Topics: exploratory-data-analysis, kaggle, lightgbm-regressor, matplotlib, numpy, pandas, python, rmse-score, seaborn, sklearn, statsmodels, timeseries-forecasting
• Language: HTML
• Homepage:
• Size: 5.42 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# AV-job-a-thon-november-2022

### Competition hosted on Analyticsvidhya

# About

### Build a machine learning/deep learning approach to forecast the total energy demand on an hourly basis for the next 3 years based on past trends.

### Initially, I thought a machine learning approach itself was enough to handle any time-series-based problem but this competition has proved that I was totally wrong.

### In one of the previous time-series-based competitions, I used the boosting regressor model and it gave me a good leaderboard rank. I tried the same approach in this competition and it become a major blunder and had given the worst rank in the private leaderboard.

### The machine learning-based approach didn't learn signals or patterns from the train data, the model learned only noise from the data.

### Finally, for this problem, the boosting algorithm well performed on the train data and failed to generalize on the test data(Overfitting!).

### I tried the seasonal decomposing linear model and it performed better than the boosting model.

### Final Competition score is 583.858113004428

### Leaderboard Rank is 207

### Evaluation Metric is RMSE.

### File information

 

 * av-job-a-thon-november-2022-eda.ipynb [![Open in Kaggle](https://img.shields.io/static/v1?label=&message=Open%20in%20Kaggle&labelColor=grey&color=blue&logo=kaggle)](https://www.kaggle.com/hari141v/av-job-a-thon-november-2022-eda)

    #### Basic Exploratory Data Analysis

    #### Packages Used,

        * seaborn

        * Pandas

        * Numpy

        * Matplotlib

* av-job-a-thon-november-2022-model.ipynb [![Open in Kaggle](https://img.shields.io/static/v1?label=&message=Open%20in%20Kaggle&labelColor=grey&color=blue&logo=kaggle)](https://www.kaggle.com/hari141v/av-job-a-thon-november-2022-model)

    #### Data Pre-processing and model. 

    #### Packages Used,

        * Sklearn

        * Pandas

        * Numpy

        * Matplotlib

        * Lightgbm

        * shap

     #### Created light gradient boosting regressor model and evaluated with RMSE. 

     #### [For more detailed information about the model.](https://github.com/hariprasath-v/AV-job-a-thon-november-2022/blob/main/Approach_AV_job_a_thon_November_2022.pdf)

     

### Lightgbm Model Feature Importances

![Alt text](https://github.com/hariprasath-v/AV-job-a-thon-november-2022/blob/main/Model%20Visualization/Lightgbm%20regressor%20top%20feature%20importances.png)

### SHAP Lightgbm Model Feature Importances

![Alt text](https://github.com/hariprasath-v/AV-job-a-thon-november-2022/blob/main/Model%20Visualization/SHAP%20Lightgbm%20regressor%20top%20feature%20importances.png)

### SHAP Top feature impact the model

![Alt text](https://github.com/hariprasath-v/AV-job-a-thon-november-2022/blob/main/Model%20Visualization/SHAP%20-%20Top%20feature%20impact%20the%20model.png)

### SHAP Top feature influences the single observation

![Alt text](https://github.com/hariprasath-v/AV-job-a-thon-november-2022/blob/main/Model%20Visualization/SHAP%20-%20Feature%20impact%20the%20single%20obsevartion.png)

### Energry Demand for Next 3 Years

![Alt text](https://github.com/hariprasath-v/AV-job-a-thon-november-2022/blob/main/Model%20Visualization/Train%20and%20Test%20plot.png)