We cluster time series through K-Medoids algorithm and train and evaluate each cluster with predictive models. We also examine the predictive performance in ...

This chapter describes the K-Medoids algorithm and various distance measurement algorithm. It also briefs on existing studies on bitcoin price prediction and ...

We consider the problem of predicting a time series on a whole interval in terms of its own past. An approach based on a wavelet decomposition and an ...

Since the development of Bitcoin, the first blockchain-based cryptocurrency, many cryptocurrencies have formed and have traded in markets.

The results of this study reveal that gated recurrent unit, simple recurrent neural network, and LightGBM methods outperform other machine learning methods, as ...

Sep 13, 2023 · Abstract: This paper proposes a unified framework for the detection of statistically significant changes in time series related to Bitcoin ...

This distance measure is used in means clustering, using this distance, distance between. 2 data points is calculated, based on this, cluster which is close ...

This present study aims to reduce the extreme value data available on Bitcoin into simple clusters based on extreme value returns.

Particularly, this study compares the accuracy of the prediction of bitcoin prices using two different models: Long-Short Term Memory (LSTM) versus Auto ...

Dec 13, 2024 · I discovered that linear models outperform recent machine learning techniques for this type of time series forecasting. Previous research has ...