- Customer churn prediction using improved balanced random forests https://sci-hub.tw/10.1016/j.eswa.2008.06.121
- Predicting Customer Churn: Extreme Gradient Boosting with Temporal Data https://arxiv.org/pdf/1802.03396v1.pdf
- Handling class imbalance in customer churn prediction https://sci-hub.tw/10.1016/j.eswa.2008.05.027
- Learning from Imbalanced Classes https://www.svds.com/learning-imbalanced-classes/
- Scikit-learn contrib Imbalanced Learn http://contrib.scikit-learn.org/imbalanced-learn/stable/index.html
- Time Series Classification from Scratch with Deep Neural Networks: A Strong Baseline https://arxiv.org/pdf/1611.06455.pdf
- Exploiting Multi-Channels Deep Convolutional Neural Networks for Multivariate Time Series Classification http://staff.ustc.edu.cn/~cheneh/paper_pdf/2016/YiZheng-FCS2016.pdf
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling https://arxiv.org/pdf/1803.01271.pdf
- Churn analysis using deep convolutional neural networks and autoencoders https://arxiv.org/pdf/1604.05377v1.pdf
- Grouped Convolutional Neural Networks for Multivariate Time Series https://arxiv.org/pdf/1703.09938.pdf
- Neural networks for algorithmic trading. Multivariate time series https://medium.com/machine-learning-world/neural-networks-for-algorithmic-trading-2-1-multivariate-time-series-ab016ce70f57
- Convolutional neural network for multi-variate time series? https://stats.stackexchange.com/questions/350840/convolutional-neural-network-for-multi-variate-time-series