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Build a Machine Learning model to predict the CTR(click through rate) of an email campaign based on the email campaigning information.

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hariprasath-v/AV_job-a-thon-august-2022

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AV_job-a-thon-june-2022

Competition hosted on analyticsvidhya.com

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Build a Machine Learning model to predict the CTR(click through rate) of an email campaign based on the email campaigning information.

Competition LB Rank: 85/959

Final Score 0.5242868399

Evaluation Metric R2 score.

File information

  • AV_job_a_thon_august_2022_EDAipynb

    Packages Used,

     * seaborn
     * Pandas
     * Numpy
     * Matplotlib
    

    Basic Exploratory Data Analysis

  • av-job-a-thon-august-2022-model.ipynb

    Packages Used,

      * Sklearn
      * Pandas
      * Numpy
      * Matplotlib
      * pycaret
    

    Data Pre-processing

    Compared multiple regression models using pycaret’s compare_models function. Then took the top 3 models based on the r2 score then blend the model by using pycaret blend_models function.

Residual Plot

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Top 3 Models

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Voting Regressor Prediction Error Plot

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Catboost Model Feature Importance Plot

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SHAP - Catboost Model Feature Importance Plot

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Build a Machine Learning model to predict the CTR(click through rate) of an email campaign based on the email campaigning information.

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