Churn prediction

I have a code written in python that include Naive Bayes, Random Forest and Decision Tree in order to predict Churn of customers in telecom industry. The accuracy is around 70%. I need to get more accuracy for those models. I need someone who could try different methods to increase that accuracy. This could be done by using better feature selection or cross-validation. Any other methods that comes to your mind, would be highly appreciated. I attached the code that needs to be improved and dataset.

Habilidades: Python, Machine Learning (ML), Arquitetura de software, Java, Algoritmo

Veja mais: churn prediction medium, customer churn prediction model in r, customer churn prediction using python, churn prediction research papers, churn prediction meaning, churn prediction dataset, churn prediction github, churn prediction kaggle

Acerca do Empregador:
( 2 comentários ) Hampton, United Kingdom

ID do Projeto: #20820058

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I am a data scientist proficient in machine learning and web scrapping. My expertise in Python and R have comes from my experience in Natural Language processing, statistical analysis, web scraping etc. I also have a s Mais

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mat i check the your attech file and i can do different method to increase that accuracy and i am wating your reply ............................

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